The world of data is changing and retailers are challenged by the increasing scale, complexity and velocity of data. The past few decades have seen exponential growth in computing and storage: driven by Moore's Law, computing power has increased dramatically, making the modern laptop more powerful than a supercomputer from 1980s. At the same time the amount of data stored has grown dramatically, thanks to rapidly declining hardware cost and the emergence of new data sources such as RFID, the web and social media.

Emerging technologies like Hadoop and MapReduce now enable customers to extract value from this growing ocean of unstructured data that was previously discarded or archived. These new technologies significantly change the economics of data processing and analysis. Hadoop dramatically reduces the cost of petascale analytics of unstructured data through the use of commodity hardware. Hadoop also shifts the analytical paradigm: its distributed computing platform, coupled with advances in machine learning, has ushered a new wave of advanced analytics with sophisticated mining tools like neural networks, genetic algorithms, graph analysis and forecasting models on petabytes of data instead of small samples. This enables customers to gain competitive advantage through the use of smart mining algorithms on all their data.

Below, are some of the case studies that use Hadoop & Microsoft Big Data platform to solve business problems:

Halo 4 Team Uses Agile, Cloud-Based Big Data Solution to Quickly Deliver BI Insight: The Halo 4000014937[1] franchise is an award-winning collection of properties that has grown into a global entertainment phenomenon. To date, more than 50 million copies of Halo video games have been sold worldwide. As developers prepared to launch Halo 4, they were tasked with analyzing data to gain insights into player preferences and support an online tournament. To handle those requests, the team used a powerful Microsoft technology called Windows Azure HDInsight Service, based on the Apache Hadoop big data framework. Using HDInsight Service to process and analyze raw data from Windows Azure, the team was able to feed game statistics to the tournament’s operator, which used the data to rank players based on game play. The team also used HDInsight Service to update Halo 4 every week and support a daily email campaign designed to increase player retention. Organizations can also take advantage of data to quickly make business decisions.

Data Services Firm Uses Microsoft BI and Hadoop to Boost Insight into Big Data: Klout wanted to give consumers, brands, and partners faster, more detailed insight into hundreds of terabytes of social-Print network data. It also wanted to boost efficiency. To do so, Klout deployed a business intelligence solution based on Microsoft SQL Server 2012 Enterprise and Apache Hadoop. As a result, Klout processes data queries in near real time, minimizes costs, boosts efficiency, increases insight, and facilitates innovation.

Yahoo! Improves Campaign Effectiveness, Boosts Ad Revenue with Big Data Solution California-based Yahoo! operates one of the most popular websites in the world, with more than 700 million 201116[1]unique visitors a month globally. The company owns and operates an online advertising exchange for the large number of customers who purchase advertising on various Yahoo! sites. They take advantage of this exchange to better target and manage their ad campaigns. Because it sought to give these customers more meaningful and useful analytical data faster, Yahoo! implemented a solution that takes data from its vast data stores within the Apache Hadoop open-source framework and ultimately moves it to Microsoft SQL Server 2008 R2. Using this solution, Yahoo! has improved campaign effectiveness, while advertisers have increased spending with Yahoo! The company also provides more relevant advertising data, and the solution’s partitioning design means faster loading of large data sets.

Thai Law Enforcement Agency Optimizes Investigations with Big Data Solution: Established to handle 4000013207[1] major criminal investigations, the Department of Special Investigation (DSI) in Thailand, needed better tools for mining large sets of structured and unstructured data. To improve investigation processes and reduce manual procedures, DSI implemented a Microsoft Big Data solution based on Microsoft SQL Server 2012 and Apache Hadoop software. Investigating officers work more efficiently with self-service business intelligence (BI) tools. And with better BI and data management capabilities, the agency has improved accuracy and shortened the time to investigate criminal cases from two years to 15 days. Next, DSI plans to expand its use of the solution and implement its own private cloud to manage the security of confidential data.