What you need to finally harness the value of your Hadoop data lake

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What you need to finally harness the value of your Hadoop data lake

Can you have too much of a good thing? If you’re not making the best use of it, definitely!

I have met many data technicians who have created a Hadoop data lake because their companies have outgrown their current Oracle, SQL server and other databases. They don’t want to lose any of their data, so they build a Hadoop infrastructure and dump it all in there. But then the question becomes, How do I derive value out of that data?

Many smart organizations using the Hadoop ecosystem will try Hive, Impala or Spark SQL to query the data lake. And many find it painfully limited and slow in performance, often waiting days or weeks to complete their analysis.
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How Kyvos 2.0 makes big data lakes ready for BI analysts

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The promise of big data is huge and transformative. But to date, big data has under delivered.

The problem is that a company’s current ability to capture data far exceeds its ability to actually use it to make smarter, more powerful business decisions.

So even as companies proliferate big data lakes using platforms like Hadoop, only a few data scientists and technical specialists can access all that valuable information to generate insights. We’re here to change that.
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