Smart companies are looking to their data, relying on analytics to uncover the answers. Yet the analytics technology landscape is evolving rapidly as well, more rapidly than most organizations and people can respond. With so much riding on the ability to extract value from data, you can’t afford to make a bet on the wrong technology.
Relational, in-memory, columnar, graph, Hadoop, and different flavors of NoSQL are available to store, retrieve and help perform advanced analytics. With vendors saying what they do best but never saying what they don’t do, where can you get a good appraisal of what technology to use for what purpose? David Lyle, a 25-year analytics veteran, laid out the current state of the art and attempt to clarify not just what to do, but also what NOT to do when planning large analytic architectures both today and into the future.
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