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GCN : August 2013
Q Hadoop is the darling of the big data world. What is it really good for? A IT shops across government are putting Hadoop through its paces in an effort to un- derstand its usefulness to the business. One of the more prevalent, emerging uses is that of a cost-effec- tive data-staging environ- ment to capture, store, and refine the ever-increasing types of data to help feed and enrich downstream analytical tools. In addition to staging, Hadoop is being leveraged with success as an efficient and effective data archive platform. Q What is it not good for? A Hadoop is fundamentally designed as a batch en- gine, capable of enormous scale at the expense of performance. Hadoop is not particularly suited to serve as an organization’s primary analytics plat- form. Today’s business environment in government is changing quite rapidly, moving far faster than ever before. As such, the analytics platform needs to move from the back office to the front office, giving them access to iterative and agile capabilities. Q What is the best combination of technologies that supports big data analytics? A From an agency perspective rather than a project or program point of view, it’s unlikely any single tech- nology can address the broad needs for an enter- prise-wide, big data analytics platform. The environ- ment needs: size, or volume. and make that data readily available to time sensi- tive analytics and business intelligence tools. as well as longer running batch-style analytics. - ety, and complexity. The breadth of these requirements can be addressed using the combination of three technologies: Ha- doop, a discovery platform, and an integrated data warehouse (IDW). Hadoop offers data staging, long- running analytics, storage for digital media (video, audio, imagery), and archiving. An IDW offers high- performance, scalable access to integrated, struc- tured, and multi-structured data. The discovery plat- form brings easy-to-use, rapid, iterative analytics to the entire environment. Q Can you offer any use cases where all three are required? A Consider cybersecurity. To effectively mitigate the risk of data loss, cyber teams need access to data quickly and reliably. The three technologies could be employed in this way: Data staging to handle the loading, stor- ing and refining of data in preparation for analytics. Integrated, shared data environment to meet the intense performance characteristics of a cyber-solution. Rapid exploration using a variety of iterative, analytic techniques. Q How would you recommend to get started? A The best advice to any IT team is to engage quickly with business users. Help them identify and quantify desired outcomes first. The more everyone under- stands what success looks like, the better positioned you will be to work with them to identify the insights needed to ensure success. While this seems like such obvious advice, in the rush to get to a big data win, often liberties are taken with best practices. My last suggestion is to be careful of starting with the assumption that any particular toolset is the an- swer. Let the business priorities drive technology, not the other way around. Big Data: Let Business Priorities Drive Tech Bobby Caudill Program director, Gover nment Industry Marketing and Solutions Teradata Cor p. Sponsored Content For more information about big data analytics, watch webcast teradata.com/ data-exploration-and-discovery Untitled-2 1 Untitled-2 1 7/25/13 1:55 PM 7/25/13 1:55 PM