Deconstructing IBM Data Engine for Analytics

Over time, we accumulate data — all sorts of data, and a lot of it. This past year my discussions around storage solution design now routinely use the word petabyte, where, just last year the same discussion would likely have used the word terabyte. Here is a statistic to consider: the amount of data accumulated every 48 hours today is about equal to the sum total of all information in human history generated until the year 2003. Big data, indeed! Like mining for gold, there is valuable information hidden in all that data, but, like gold ore, that data has to be processed for the value to be extracted.

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Big Data Toolset Smackdown

If you’ve spent more than five minutes researching big data, you’ve already come across technologies like Hadoop, BigQuery, EMR and RedShift, and you may even know what OLAP and NoSQL means and where they fit in. What you may not have been exposed to, however, is the next and very important level down the rabbit hole—technologies like Tableu, Microstrategy, QlikView, Hive and Impala. Let’s take a look at each of these technologies and see where they fit and how they compare to each other.

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