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SafeAssign Originality Report Summer 2020 - InfoTech Import in Strat Plan (ITS-83… • Final Portfolio Project
%57Total Score: High risk Santhosh Kumar Gorantala
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Running Head: DATA WAREHOUSE
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DATA WAREHOUSE
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DATA WAREHOUSE
Santhosh Kumar Gorantala
University of Cumberlands
Introduction
Data warehouse, big data, and green computing are three of the most talked-about and trendy topics in the world of technology. They are of
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great importance, and each plays a very valid role. Below is an elaborative discussion of what these terms mean and how they are used. Prompt no. 1 Data warehouse Architecture A data warehouse is a big collection of data stored from various sources, and this process is known as data ware- housing. Data warehouses collect data to analyse, and criticality is scrutinizing data to generate results and reports (Zimanyi & Vaisman, 2014). Mul- tiple queries are run on data warehouses to generate reports. Data warehouses are most famously used for business intelligence activities, mainly consisting of analytics. Businesses have data warehouses which contain all the historical and present data related to their business, customer, and products which will come as useful whenever they need. The technique of data warehousing has become a very big essential in the management of all academic and extracurricular data available inside a university or any other educational institutes. As universities acquire an extremely large col- lection of data related to students, staff, courses, and other such activities, there is a very dire need for every university to have their data ware- house. There are multiple, very efficient data warehouses available right now in the market. Almost every big technology company is investing in data warehousing products. The two most efficient, in my opinion, for universities are Amazon Redshift and Google Big Query. Data has huge importance in today's business world right now. It is given the status of gold for the latest technological organizations. The biggest trade be- tween such technological organizations is data. Big clusters of data are shared among several tech companies every day. Data has made it pos- sible for every social media site to act in a cohesive pattern. Data plays a very big role in developing and shaping a business. Because of Data stored in their data warehouses, an organization comes to know more about what the market has demand for and what their customers prefer and what they dislike. Data warehouse architecture is explained as the method through which it is classified as to how end-users will interact with the data warehouse. It explains how data will be analysed and presented comprehensively to the organizations utilizing the data warehouse. Data ware- house basically contains five main components, which together make the data warehouse operable, functional, and reliable to use. These five com- ponents are based on the Relational Database Management system, and they are data warehouse database; Extract, Transform, and Load (ETL) Tools; Metadata; Query Tools and Data Marts. The Data warehouse database is the main component of the data warehouse architecture. It is the database on which the data is stored. It is a relational database that is usually designed to perform transactions on the data. As the transaction is not one of the demands of data warehouses, the database in this scenario is little modified to the desired use. A mostly multidimensional data- base (MDDB) is used to remove any deficiency in RDMS. Extract Transform and Load (ETL) tools are also a major component, and they are used to perform every conversation and transformations on data, which is necessary for warehousing to derive a uniformed model of data. There is anoth- er type of tool used by organizations called query tools, which allows the user to interact with the data. These tools help organizations to perform analysis and generate reports. Another major component in metadata which basically means data about the data. It is the information about the data which is stored in the data warehouse. It contains the source of the data, size, and date at which it was added and other such information. The last major component is data marts, which are used to present data to the end-users. In order to fully arrange and analyse data in a data ware- house, the data is usually transformed into a suitable form. This happens with the help of ETL tools. Data is scattered and mismanaged before feed- ing it into the data warehouse. Hence, the transformation of data is necessary. There are three techniques used for this transformation. The trans- formation is done by either using SQL or by using PL/SQL or by using Table functions. There are currently many trends that are gaining popularity in the data warehouse market. One such trend is using column-based data storage. Using a column-based data storage helps in fast query pro- cessing speed as well as takes less space on the disk. So, utilizing this method, the data warehouse size can be increased, and the speed will also get better. Another famous trend is automating the implementations and management of the data warehouse. Typically, in order to manage data ware- house, businesses would need one or two IT personnel whose whole job was to maintain the data warehouse.
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But now there are data warehouses available which are self-dependent and can greatly help in reducing operational cost. Businesses would not need to hire special staff (Naeem, 2018). Prompt no 2. Big Data Big Data is a term that refers to dealing with a large chunk of data. It means to collect data, analyse it, and conclude result and important information from it. These huge clusters of data are scrutinized to generate patterns and trends from it (Lane, Stodden, Bender, & Nissenbaum, 2014). These patterns and trends are proved very helpful in designing an endorsement around it. Only when big organizations knew what their customers want, can they actually deliver the required product in a way their customers de- sired? This all has become very easy through the procedure of data mining and analysing as now the companies just have to buy data as com- pared to conducting surveys and going through an excruciating process of research and analysis. There are many specific companies that do the work of gathering and selling data. Equifax is one such company. Their main job is to collect data about a specific individual or a specific demo- graphic and sell it to the highest bidder. Equifax is a company that can specifically provide you with all the information about a credit score of a spe- cific person. This comes very handily and helpful for the marketing team of any bank or any other financial institution. In 2017, Equifax alone had made 3.1 billion dollars in revenue just by selling credit data to other companies (Bloor, 2018). Similarly, Data sift is a social media data supplier. It collects and distributes every information of an individual related to his social media profiles (Brown, 2015). Data related to social media is one of the biggest market available for data right now. Facebook makes around 46 million dollars to 92 million dollars on selling personal data of one sin- gle individual (Seth, 2018). Personal data has the biggest value in the market, and companies like Facebook and Goggle, where we as users, con- stantly upload and put our personal details earns quite a lot from just selling this data further. Big data has a tremendous effect on the global economy. Every business that is booming right now is related to selling or analysing data is some form. Data is considered to be of great value in any kind of business or cooperation. It is the biggest investment that reaps the best benefits for businesses. The biggest trade between such technological organizations is data. Hence, the companies that provide data run the economy (Green & Panjiva, 2013). Big data is putting a lot of pressure on businesses to invest in high-class technology. By utilizing big servers and data analytics techniques to handle big data, the companies are investing a lot of capital. Big data demands that the business which utilizes this technology has huge servers that could store all the data and handle all the processing that would be performed on it. Many businesses are now moving towards cloud computing as their main storage and get- ting rid of any servers they installed. The cloud itself is a very expensive means of storage, and adding that with the storage capacity for big data ac- tually makes the cost of installation extremely high. As we have concluded that data is considered to be a very important entity in any business right now. Data mining and selling is the biggest trend right now, which every company is picking up every day. It is a very profitable business. Prompt no. 3 Green Computers The biggest discussion that is prevailing right now in the world is the discussion of climate change and being envi- ronmentally friendly. Everyone is now moving towards being eco-friendlier and always looking for alternatives to everyday products that would not harm the environment in any manner. Several businesses now see a big market opportunity in eco-friendly and socially aware products and hence moving towards making their companies more socially acceptable by going towards the green route. The computing world is also starting to realize that the way the computers are developed, used, and then discarded is creating a big problem for the environment and causing a strain on an al- ready complex problem of climate change. Hence, the computing world is also moving towards an eco-friendlier and environmentally conscious method of using and managing computers and all their resources (Jain, Mishra, Peddoju, & Jain, 2013). There are multiple methods through which data centres can also move towards a greener choice and a better alternative to the already present options. One such method is analysing the us-
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data centres can also move towards a greener choice and a better alternative to the already present options. One such method is analysing the us age of the whole system. Most of the time, there are individual systems that are always running on the background without the need for it. These systems can really lack up energy usage for the whole data centres. Hence, it is important to fully analysed the data centre and ensure that only the most needed machine and the system are using energy and unnecessary systems are always off so that they do not waste energy.
There are several ways through which energy can be saved by using better alternatives. Like using low voltage lights and reducing the waste is such ways. The best alternative to the cooling machine would be to make data centres in locations that are naturally cooler (Struckmeier, 2018). Hence, the need for coolers in the data centres to keep the servers cool will drastically decrease. As discussed earlier, several companies are now moving towards an eco-friendlier alternative to their usual way of operating. Facebook, Google, Apple, and Microsoft all have pledged to be eco-friendlier and to be more conscious of their energy waste. Out of all these, Google has actually invested the most into making their companies eco-friendly and utilizing their energy in the most efficient manner. One such example of their actions is easily visible when Google designed an artificially intelli- gent system called DeepMind, which with the help of machine learning, can judge whether the temperature is high or not. This DeepMind AI system only sets the cooling on when it realizes that temperature is high. This is the best option they could have installed in their data centres as it helps to stop wasting energy unnecessarily and only uses cooling when needed. By doing this, Google has reduced 40% using energy for its cooling and air conditioning (Babcock & Franklin Jr., 2016).
References
Zimanyi, E., & Vaisman, A. (2014). Data Warehouse Systems: Design and Implementation. Springer. Babcock, C., & Franklin Jr., C. (2016, Au- gust 5). Green Data Centers: 8 Companies Doing Them Right. From Inforoamtion week: https://www.informationweek.com/data- centers/green-data-centers-8-companies-doing-them-right/d/d- id/1326498#:~:text=Facebook%2C%20Apple%2C%20Google%2C%20eBay,may%20be%20forced%20to%20follow. Bloor, R. (2018, March 21). How Much is Your $$$Data Worth? From Medium.com: https://medium.com/permissionio/how-much-is-your-data-worth-c28488a5812e
Brown, M. S. (2015, September 30). When and Where To Buy Consumer Data (And 12 Companies Who Sell It). From Forbes: https://www.- forbes.com/sites/metabrown/2015/09/30/when-and-where-to-buy-consumer-data-and-12-companies-who-sell-it/#7b7198843285
Green, J., & Panjiva. (2013, March). Big Data: The Key to Economic Development? From Wired: https://www.wired.com/insights/2013/03/big-data-the-key-to-economic-development/ Jain, A., Mishra, M., Peddoju, S. K., & Jain, N. (2013). Energy efficient computing- Green cloud computing. 2013 International Conference on Energy Efficient Technologies for Sustainability. Lane, J., Stodden, V., Bender, S., & Nissenbaum, H. (2014). Privacy, big data, and the public good. New York: Cambridge University Press. Naeem, T.
(2018, November 12). Industry Trends: What’s Next in the World of Data Warehousing. From Datawarehouse info: https://dataware- houseinfo.com/industry-trends-whats-next-in-the-world-of-data-warehousing/ Seth, S. (2018, April 11). How Much Can Facebook Potentially Make from Selling Your Data? From Investopedia: https://www.investopedia.com/tech/how-much-can-facebook-potentially-make-selling-your- data/ Struckmeier, J. (2018, February 16). 5 Steps to a Green Data Center. From Facilities net: https://www.facilitiesnet.com/datacen- ters/contributed/5-Steps-to-a-Green-Data-Center--40635
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University of the Cumberlands
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Data warehouse, big data, and green computing are three of the most talked-about and trendy topics in the world of technology.
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Data warehouse, big data, and green computing are some of the most im- portant transformative strategies in information technology today
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There are multiple, very efficient data warehouses available right now in the market.
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There are multiple data mining soft- ware and tools available right now in the market
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Data has huge importance in today's business world right now.
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Data has a huge importance in to- day’s business world right now
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It is given the status of gold for the latest technological organizations. The biggest trade between such technological organizations is data.
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It is given the status of gold for the latest technological organizations The biggest trade between such technological organizations is data
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Student paper
Big clusters of data are shared among several tech companies every day. Data has made it possible for every social media site to act in a cohesive pattern. Data plays a very big role in developing and shaping a business. Because of Data stored in their data warehouses, an organiza- tion comes to know more about what the market has demand for and what their customers prefer and what they dislike.
Original source
Big clusters of data are shared among several tech companies every day Data has made it possible for every social media site to act in a cohesive pattern Data plays a very big role in developing and shaping a business It is because of Data mining that an organization comes to know more about what the market has de- mand for and what their customers prefer and what they absolutely dislike
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Extract, Transform, and Load (ETL) Tools;
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Extract-Transform-Load (ETL) Tools
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The Data warehouse database is the main component of the data ware- house architecture.
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Bus architecture is a component of a data warehouse that helps in the de- termination of the identified data flow in the warehouse
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It is the information about the data which is stored in the data warehouse.
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Information Processing - A data warehouse allows to process the data stored in it
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One such trend is using column- based data storage.
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Column based data storage
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Big Data Big Data is a term that refers to dealing with a large chunk of data. It means to collect data, an- alyse it, and conclude result and im- portant information from it.
Original source
Big Data is a term that refers to deal- ing with a large chunk of data It means to collect data, analyse it, and conclude result and important infor- mation from it
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These huge clusters of data are scru- tinized to generate patterns and trends from it (Lane, Stodden, Ben- der, & Nissenbaum, 2014). These patterns and trends are proved very helpful in designing an endorsement around it. Only when big organiza- tions knew what their customers want, can they actually deliver the required product in a way their cus- tomers desired?
Original source
These huge clusters of data are scru- tinized to generate patterns and trends from it (Lane, Stodden, Ben- der, & Nissenbaum, 2014) These pat- terns and trends are proved very helpful in designing an endorsement around it Only when big organiza- tions knew what their customers want, can they actually deliver the required product in a way their cus- tomers desired
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This all has become very easy through the procedure of data min- ing and analysing as now the compa- nies just have to buy data as com- pared to conducting surveys and go- ing through an excruciating process of research and analysis.
Original source
This all has become very easy through the procedure of data min- ing and analysing as now the compa- nies just have to buy data as com- pared to conducting surveys and go- ing through an excruciating process of research and analysis
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Original source
Research There are many specific companies who do the work of gath- ering and selling data Equifax is one such company Their main job is to collect data about a specific individ- ual or a specific demographic and sell it to the highest bidder Equifax is a company which can specifically provide you with all the information about a credit score of a specific person
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This comes very handily and helpful for the marketing team of any bank or any other financial institution. In 2017, Equifax alone had made 3.1 billion dollars in revenue just by sell- ing credit data to other companies (Bloor, 2018).
Original source
This comes very handily and helpful for the marketing team of any bank or any other financial institution In 2017, Equifax alone had made 3.1 billion dollars in revenue just by sell- ing credit data to other companies (Bloor, 2018)
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Original source
The biggest trade between such technological organizations is data Hence, the companies who provide data run the economy (Green & Pan- jiva, 2013) Big data is putting a lot of pressure on businesses to invest in high-class technology By utilizing big servers and data analytics tech- niques to handle big data, the com- panies are investing a lot of capital
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As we have concluded that data is considered to be a very important entity in any business right now. Data mining and selling is the big- gest trend right now, which every company is picking up every day. It is a very profitable business.
Original source
As we have concluded that data is considered to be a very important entity in any business right now Data mining and selling is the biggest trend right now, which every compa- ny is picking up every day It is a very profitable business
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Retrieved from https://www.infor- mationweek.com/data- centers/green-data-centers-8-com- panies-doing-them-right/d/d- id/1326498#:~:text=Facebook%2C% 20Apple%2C%20Google%2C%20e- Bay,centers%20toward%20all%2D- green%20operations
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(2018, November 12).
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(2018, November 12)
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(2018, February 16).
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