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Planning, skills needed to navigate Hadoop data lakes
In the business intelligence and analytics world, data lakes are their own region -- one in which today's multifarious forms of information can be stored in their native forms until used -- and cheaply at that. But these vast storage repositories, which are based on open source Apache Hadoop are not for those seeking rest and recreation. They take serious work -- and often sought-after skills -- to build and maintain.
In this guide, SearchDataManagement peers across several types of data lakes to discover how different organizations today are implementing them. First, editor Craig Stedman talks to three companies that have taken the dive -- and learns about the challenges and benefits presented to each. Next, reporter Jack Vaughan tells one executive's story -- how a Hadoop-based system opened new doors for his company. Finally, Vaughan quizzes Forrester analyst Mike Gualtieri on whether data lakes can compete with data warehouses to quench organizations' thirst for storing and analyzing business data.
Table Of Contents
- Data lakes can drag unprepared users under
- Hadoop fuels TrueCar’s data-driven business model
- Data lakes must wash out the mess