CIS 500 CASE STUDY 1

Topics: Microsoft, Business intelligence, Microsoft Office, Microsoft Word / Pages: 4 (927 words) / Published: Jun 8th, 2015
CIS 500 - CASE STUDY – The Big Data Challenges

by
CIS 500
Professor:
October 28, 2013

CASE STUDY 1
Introduction
In year 2010, Volvo Car Corporation separated from Ford and integrated the cloud infrastructure into its network. They needed to build up a new individual Information Technology infrastructure that could provide better business, increase communication capabilities and improve collaboration. This paper is going to explicate how Volvo Car Corporation transforms data into knowledge, it will identify the real-time information systems implemented and evaluate the impact of these implementations, and it will argue how the Big Data strategy give Volvo Car Corporations a competitive advantage. In 2010 the environment at Volvo Corporation was kind of difficult, hard to manage, and expensive and Volvo wanted to improve its BI (Business Intelligence) capabilities. Volvo’s IT architect stated: “All the products out there have been purchased by some department at some time in history, and we are trying to consolidate and simplify our BI infrastructure” (Microsoft, 2012). Microsoft web site from (Microsoft, 2012) stated : “To address these challenges, Volvo is deploying a pilot solution based on Microsoft SQL Server 2012 Business Intelligence data management software and related BI technologies, including Microsoft SharePoint Server 2010 and Microsoft Office 2010. One of the big reasons for choosing Microsoft is that Microsoft products are designed to work well together. “We strive to keep down the number of technologies, and since Microsoft ensures the interoperability of those applications, we don’t have to worry about that,” the IT architect says. According to Asthna, 2011, Volvo car maker collects terabytes of data from embedded sensors in their cars—from their customer relationship management (CRM) systems, from dealerships, and from their factory floors. These data streams are combined and analyzed to yield early predictive

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