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SafeAssign Originality Report Fall 2020 - Business Intelligence (ITS-531-M41) - Full Term • Week 10 Assignments
%63Total Score: High riskManikanta Korasika Submission UUID: 4575e41f-5bb6-24f9-83b9-79d6bd38b7ef
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1 Highest Match
63 % BigData.Week-10.docx
Average Match
63 % Submitted on
11/01/20 10:41 AM EST
Average Word Count
731 Highest: BigData.Week-10.docx
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Running Head: BIG DATA 1
BIG DATA 5
Big Data
002837061
University of the Cumberlands
Dr. Abiodun Adeleke (Abbey) ITS-531-M41
11/01/2020
Big Data
1. Big Data meaning, importance and where it comes from. It is a term that defines the large volume of data, both unstructured and structured, that inundates a business
daily. (Violino, 2019) But it is not the amount of data that is critical. Big data can be analyzed for insights that leads to strategic management moves and better decisions. Big
data assists the company in creating new opportunities in growth and absolutely new categories of organizations that can incorporate and analyze industry data. These organizations have enough information on the suppliers and buyers, consumer preferences, and products and services captured and analyzed. The data that comprise big
data stores can come from various sources, including social media, scientific experiments, web sites, and other devices. 2. The future of Big Data and if it will lose its
popularity
Big Data can develop gradually at an expeditious rate. The "Big Data" buzzword may alter to something else, though the tendency toward increased abilities of computing,
techniques of analytics, and management of data of a high volume of diverse information will carry on. 3. Meaning of Big Data analytics and how it differ from regular
analytics. Big Data analytics is the analytics that is applied to architectures of Big Data. This is a new model; to maintain the computational requirements of Big Data, some
innovative and new analytics computational platforms and methods have been developed. Big Data analytics differ from other usual analytics, which incline to pay attention on technologies of relational database.
4. The critical success factors of Big Data analytics
They are; a) A precise business goal. Business investment has to be created for the business good, but not for the sake of only advancements in technology. b) Committed and strong sponsorship. c) Alignment between IT and business strategy. Analytics should play the role that is enabling in executing the business strategy successfully. d) A
decision-making culture that is based on fact. In a culture of decision making that is fact-based, the numbers instead of intuition, gut feeling, or assumption drive decision making. e) A strong data infrastructure. Success needs marrying the new with the old for a complete infrastructure that works interactively. 5. Summarize the findings of Big Data in
sports. Using the TUN site, I found one article known as data ball describing how data analytics assists in enhancing players of basketball. The Data analytics that is used in
this case are expected progression value (EPV). It is used to predict what will happen next depending on the situations of the game; it uses stats like past strategies, players, and formations. Obtaining all of this new data does not mean that basketball will completely change until they totally have insights on using the new data. At the moment, it will give more intuition into the flaws of players and strategies. Like in basketball, sports analytics is enhancing football games. The NFL utilizes all these new facts to understand
exactly all the involved data in a play. Like the distance a player runs, the speed of the football in the air, and the speed the players run at. The NFL does not only concentrate on enhancing the players but on assisting those who are watching to have a better insight into what is going on in each game. The NFL is committing to gaining more data. They
use a production truck out of each game in collecting the data and creating stats so that the broadcaster can use to put emphasis on the level of play. This ends up being a lot of data of every player, so most of the sports utilize it to make decisions on when to substitute people and who is better for each situation. For every sport, data analytics is enhancing the game by giving audience members hard stats or improving players. All the used application is for doing sports to be more significant (Teradata, 2020).
References
Teradata. (, 2020). Data Analytics Online Resources | Teradata University for Academics. https://academics.teradata.com/ Violino, B. (2019, October 18). What
is big data analytics? Fast answers from diverse data sets. InfoWorld. https://www.infoworld.com/article/3220044/what-is-big-data-analytics-fast-answers-from-diverse-
data-sets.html
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BIG DATA 1
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1.What is big data
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5 Elements Of Big Data
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University of the Cumberlands
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The University of Cumberlands
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11/01/2020
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(2020, February 11)
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It is a term that defines the large volume of data, both unstructured and structured, that inundates a business daily.
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Big data is a term which defines the large data volumes, both the unstructured and structured data, which inundates businesses on a daily basis
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Big data can be analyzed for insights that leads to strategic management moves and better decisions.
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Big data can be analyzed for insights that lead to better decisions and strategic business moves
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The data that comprise big data stores can come from various sources, including social media, scientific experiments, web sites, and other devices.
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Big data comes from sources that include social media, mobile apps, scientific experiments, web sites, and other devices on the internet of things
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The future of Big Data and if it will lose its popularity
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Q 2) In the future, big data will not lose its popularity compared to other things
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The "Big Data"
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The importance of "Big Data"
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Meaning of Big Data analytics and how it differ from regular analytics. Big Data analytics is the analytics that is applied to architectures of Big Data.
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How does it differ from regular analytics Big Data analytics is analytics applied to Big Data architectures
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to maintain the computational requirements of Big Data, some innovative and new analytics computational platforms and methods have been developed.
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in order to keep up with the computational needs of Big Data, several new and innovative analytics computational techniques and platforms have been developed
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The critical success factors of Big Data analytics
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What are the critical success factors for Big Data analytics
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c) Alignment between IT and business strategy. Analytics should play the role that is enabling in executing the business strategy successfully. d) A decision-making culture that is based on fact.
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Alignment between business and strategy Analytics should play the enabling role in successfully executing the business strategy Fact-based decision-making culture
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e) A strong data infrastructure. Success needs marrying the new with the old for a complete infrastructure that works interactively.
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Strong data infrastructure Success requires marrying the old with the brand new for a holistic infrastructure that works synergistically
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The Data analytics that is used in this case are expected progression value (EPV).
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In this case, data analytics uses the expected progress value (EPV)
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Like in basketball, sports analytics is enhancing football games. The NFL utilizes all these new facts to understand exactly all the involved data in a play. Like the distance a player runs, the speed of the football in the air, and the speed the players run at.
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Football analytics applications of Big Data in sports, like basketball, sports analytics is improving football games The NFL utilizes all these new facts to know precisely all the data involved in a play Such as distance a player runs, the speed they run at, the speed of the ball in the air
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They use a production truck out of each game in collecting the data and creating stats so that the broadcaster can use to put emphasis on the level of play. This ends up being a lot of data of every player, so most of the sports utilize it to make decisions on when to substitute people and who is better for each situation. For every sport, data analytics is enhancing the game by giving audience members hard stats or improving players.
Original source
They use a production truck outside of each game to assemble the data and create statistics so the broadcaster can use to emphasize the level of play This ends up being a lot of data of each player, so most sports use it to decide when to substitute people and who is better for each scenario In every sport, data analytics is advancing the game whether it is by improving player or giving audience members hard statistics
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Data Analytics Online Resources | Teradata University for Academics.
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Data Analytics Online Resources | Teradata University for Academics
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https://academics.teradata.com/ Violino, B.
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https://academics.teradata.com/ SHARDA, R
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(2019, October 18).
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(2019, October 18)
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What is big data analytics?
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What is big data analytics
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Fast answers from diverse data sets.
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Fast answers from diverse data sets
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https://www.infoworld.com/article/3220044/w hat-is-big-data-analytics-fast-answers-from- diverse-data-sets.html
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https://www.infoworld.com/article/3220044/w hat-is-big-data-analytics-fast-answers-from- diverse-data-sets.html
