Kinds of Big Data: Foundations of Business Intelligence Case Study

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When it comes to collecting big data, the British Library’s approach can be reviewed first. IBM and the British Library collaborated to build a big data system. The Library collects large volumes of unorganized Web data to make them extracted, annotated, and graphically analyzed with the aid of IBM BigSheets (Big data, big rewards, n.d.). Customers can see search results, for instance, as a pie graph. Because it is based on the Hadoop architecture, IBM BigSheets is able to process massive volumes of data rapidly and effectively.

The following entity, State and Federal Law enforcement, collects big data to identify trends in criminal behavior that might be challenging to identify in smaller samples. This includes connections between time, possibility, and entities or less apparent connections between people and crime syndicates (Big data, big rewards, n.d.). Criminals and crime syndicates are progressively coordinating and carrying out their crimes online. With the use of new technologies, authorities may now examine data from a variety of sites and use analytics to forecast potential crime trends.

The NYPD can easily access information from the Real Time Crime Center data warehouse because of the system’s search functionality. The given system was created with the collaboration between IBM and the NYPD (Big data, big rewards, n.d.). A criminal’s photo and details about past convictions, as well as locations and maps, may be shown on a projection screen in a matter of seconds or immediately transmitted to responding cops at a crime scene.

As for other organizations, such as Vestas, a total of 178 factors are collected. This includes pressure changes, dampness, wind speed and direction, temperatures, as well as other historical corporate data, which are stored in the 2.8 petabyte-sized company wind archive (Big data, big rewards, n.d.). Global deforestation measurements, satellite photos, geographical data, and information on lunar cycles and tides are all planned additions by Vestas in the future.

Finally, big data services are also being used by businesses to study customers’ perceptions. For instance, the world’s largest vehicle rental company Hertz collects information from online surveys, letters, texts, website traffic trends, and data produced at all of its 8,300 sites across 146 different countries (Big data, big rewards, n.d.). Considering that today data is stored centrally rather than at each branch, the organization can analyze data more quickly and respond to client feedback and shifts in perception more quickly.

Reference

Big data, big rewards. (n.d.). In Chapter 6: Foundations of Business Intelligence.

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IvyPanda. (2024, January 15). Kinds of Big Data: Foundations of Business Intelligence. https://ivypanda.com/essays/kinds-of-big-data-foundations-of-business-intelligence/

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IvyPanda. 2024. "Kinds of Big Data: Foundations of Business Intelligence." January 15, 2024. https://ivypanda.com/essays/kinds-of-big-data-foundations-of-business-intelligence/.

1. IvyPanda. "Kinds of Big Data: Foundations of Business Intelligence." January 15, 2024. https://ivypanda.com/essays/kinds-of-big-data-foundations-of-business-intelligence/.


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IvyPanda. "Kinds of Big Data: Foundations of Business Intelligence." January 15, 2024. https://ivypanda.com/essays/kinds-of-big-data-foundations-of-business-intelligence/.

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