Essential Guide

This Essential Guide is a collection of articles, videos and other content selected by our editors to give you a comprehensive view of this topic.

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

Do you have big ideas about big data? Resources in this guide offer advice on big data strategies and big data management tips from experienced users.

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.

Big data strategy

1. Advertising firm attracts clients with big data strategy

The search advertising company adMarketplace processes billions of ad requests daily in near real time using a pay-per-click platform. Due partly to the high level of data customization it offers to advertisers, adMarketplace processes 100 gigabytes of data per hour. The first article below explains how the company implemented a platform combining a traditional data warehouse and a NoSQL database to power the big data environment that feeds its search syndication system. Other stories in this section offer more insights into managing and using big data and how it fits into the data warehousing and data governance process.

Successful big data projects

2. Sprint's big data project highlighted at IBM conference

At IBM's most recent Information on Demand conference, an executive from Sprint presented information on the telecommunications company's efforts to harness big data to gain new insights on how customers are using its network. An IBM vice president also offered guidance for other companies interested in tackling big data initiatives. Below, find related articles that explore IBM's own use of big data tools and provide advice on developing and implementing big data strategies.

Big data tools

3. Managing 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.

Data warehouses & big data

4. Big 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.


5. Big data terminology

Terms like "big data" are used in a variety of contexts. Check out the technical definitions here.