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Big data applications: Real-world strategies for managing big data

Last updated:June 2013

Editor's note

Big data management strategies and best practices are still evolving, but joining the big data movement has become an imperative for companies across a wide variety of industries. This guide delves into the experiences of early-adopter companies that have already deployed big data applications and technologies. IT professionals, C-level executives and industry analysts offer insights into what strategies work on big data projects and how to best integrate big data management initiatives with related processes such as data warehousing, data governance and data analytics.

The following stories explore the steps these companies took to set up big data systems and to update their approaches as needed. Readers will find practical information on implementing big data strategies, mixing Hadoop clusters and conventional data warehousing tools, incorporating big data analytics into the process and translating big data ideas into successful deployments.

1Managing online data: comScore explains big data analytics move

In an effort to improve upon its big data analytics program, Web analytics and customer intelligence services provider comScore Inc. moved from one Hadoop distribution to a competing platform. The lead article below explores the reasons why and offers advice on big data analytics and management best practices. The other related stories offer additional insight and information on Hadoop and other big data technologies.

2Big data applications create new opportunities -- and challenges

Catalina Marketing Corp., which tracks and analyzes the shopping activities of consumers, was managing huge data sets long before big data became a C-suite phrase. In the first article in this section, Catalina's now-retired CIO offers advice to organizations that are launching big data management and analytics strategies, highlighting the importance of using distributed systems to lighten the load on data warehouses. Other users and analysts weigh in as well. The related stories below further explore ideas for effectively combining data warehousing and big data management technologies.

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