Big Data Is Still Hard. Here’s Why

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We’re over a decade into the big data era that emerged from the tectonic collision of mobile, Web 2.0, and cloud forces. Bolstered by progress in machine learning, we stand at the cusp of a new AI era that promises even greater automation of rudimentary tasks. But despite the progress in AI, big data remains a major challenge for many enterprises.

There are lots of reasons why people may feel that big data is a thing of the past. The biggest piece of evidence that big data’s time has passed may be the downfall of Hadoop, which Cloudera once called the “operating system for big data.” After acquiring Hortonworks, Cloudera and MapR Technologies became the two primary backers of Hadoop distributions. The companies had actually been working to distance themselves from Hadoop’s baggage for some time, but they apparently didn’t move fast enough for customers and investors, who have hurt two companies by holding out on (Hadoop) upgrades and investments.

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