TODAY THERE ARE MANY NEWS BUSINESSES WHO HAVE
GAINED BY MEANS OF ADOPTING NEW STRATEGIES
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
Amidst all of the hobby and desire regarding statistics-driven journalism, there is one query that
newsrooms are continually curious about: what are the business fashions? While we should be cautious
about making predictions, a examine the latest history and contemporary country of the media industry
can help to present us a few perception. Today there are many news businesses who have gained by
means of adopting new strategies. Terms like “facts journalism”, and the newest buzzword “facts
technology” may additionally sound like they describe something new, however this isn't always strictly
authentic. Instead, these new labels are just ways of characterizing a shift that has been gaining strength
over a long time.
Many reporters seem to be unaware of the dimensions of the sales that is already generated thru
information collection, facts analytics, and visualization. This is the commercial enterprise of records
refinement. With records tools and technologies, it is increasingly more feasible to shed light on rather
complex troubles, be this global finance, debt, demography, education, and so on. The term “business
intelligence” describes a selection of IT principles aiming to provide a clear view on what is happening in
business organizations. The massive and profitable organizations of our time, together with McDonalds,
Zara or H&M, depend on consistent data monitoring to turn out a profit. And it really works quite well for
them.
What's changing right now could be that the equipment developed for this area is now becoming available
for other domains, consisting of the media. And there are journalists who get it. Take Tableau, a company
offering a set of visualization tools. Or the “big data” movement, wherein technology companies use
(often open-source) software applications to dig through piles of data, extracting insights in milliseconds.
These technologies can now be applied to journalism. Teams at The Guardian and The New York Times
are constantly pushing the bounds on this emerging field. And what we're currently seeing is just the tip
of the iceberg.
But how does this generate cash for journalism? The big, international marketplace that is currently
opening up is all about the transformation of publicly available data into something that we can process:
making data visible and making it human. We need to have the ability to relate to the big numbers we
hear every day in the news — what the millions and billions mean for each of us.
There are a number of very seasoned table data-driven media companies, who have definitely
implemented this principle earlier than others. They enjoy healthy growth rates and sometimes
astonishing profits. One example: Bloomberg. The company operates about 300,000 terminals and
delivers financial data to its customers. If you are in the money business, this is a power tool. Every
terminal comes with a color-coded keyboard and up to 30,000 options to look up, analyze, compare, and
help you to decide what to do next. This core business generates an estimated US $6.3 billion per year, at
least this is what a piece by The New York Times estimated in 2008. As a result, Bloomberg has been
hiring reporters left, right, and center, they bought the venerable but loss-making “Business Week” and so
on.
Another example is the Canadian media conglomerate today referred to as Thomson Reuters. They started
with one newspaper, sold up some of well-known titles in the UK, and then decided two decades ago to
leave the newspaper business. Instead, they have grown based on data services, aiming to provide a
deeper perspective for clients in a number of industries. If you worry about how to make money with
specialized data, the advice would be to just read about the company’s history in Wikipedia.
And take a look at The Economist. The magazine has built an exceptional, influential brand on its media
side. At the same time, the “Economist Intelligence Unit” is now more like a consultancy, reporting about
relevant trends and forecasts for almost any country in the world. They are employing hundreds of
journalists and claim to serve about 1.5 million customers worldwide.
And there are numerous niche data-driven services that could serve as inspiration: eMarketer in the US,
providing comparisons, charts, and advice for everyone interested in internet advertising. Stiftung
Warentest in Germany, an institution looking into the quality of products and services. Statista, again
from Germany, a start-up helping to visualize publicly available data.
Around the world, there is currently a wave of startups in this sector, covering a wide range of areas —
for example, Timetric, which aims to “reinvent business research”, OpenCorporates, Kasabi, Infochimps,
and data market. Many of these are arguably experiments, but together they can be taken as an important
sign of change.
Then there is the public media, which in terms of data-driven journalism is a sleeping giant. In Germany
€7.2 billion per year are owing into this area. Journalism is a unique product: if done properly, it is not
just about making money but serves an important function in society. Once it is clear that data journalism
can offer better, more reliable insights more easily, some of this money will be used for new jobs in
newsrooms.
With data journalism, it is not just about being first but about being a trusted source of information. In this
multichannel world, attention can be generated in abundance, but trust is an increasingly scarce resource.
Data journalists can help to collate, synthesize, and present various and often difficult sources of data in a
way that gives their audience real insights into complex issues. Rather than just recycling press releases
and retelling stories they’ve heard elsewhere, data journalists can deliver readers a clear, understandable,
and preferably customizable perspective with interactive graphics and direct access to primary sources.
Not trivial, but truly valuable.
