Analysis: Hadoop in the enterprise | #BigDataNYC
The Hadoop ecosystem is evolving at a staggering pace, with SQL querying already fading into the background as real-time analytics and YARN take the center stage, spawning new use cases and broadening the application of Big Data in the enterprise. SiliconANGLE founder John Furrier and Wikibon’s Dave Vellante and Jeff Kelly took a break from Day 3 of Big Data NYC to recap the latest industry milestones and examine where the market is headed next.
Organizations are increasingly leveraging Hadoop to solve business problems, a trend that is prompting large vendors such as EMC to throw their hats into the Big Data ring. The competition is heating up as more players enter the fray, Vellante observes, moving beyond infrastructure and distributions. But the shortage in commercial-grade, off-the-shelf analytical apps poses a bottleneck to Hadoop adoption that is slowing down growth, he continues.
After going over recent launches, including Hortonworks Data Platform 2.0, Cloudera’s rivaling Enterprise Data Hub and CloudStory, Furrier highlights that BI is taking precedence over data warehousing. Kelly points out that business intelligence is a “loaded term” that cannot necessarily be used to describe the new paradigm of putting insights in the hands of everyday end-users.
“There is definitely value in a dashboard and [a] report, and we’re still gonna see the need for it, but really it’s about putting intelligence in context for end-users,” Kelly says.”Put in context what they do every day, make it easy for them to understand what’s the next best option, what decision should I make, what action should I execute.”
Getting back to Hadoop, Vellante notes that the distribution wars are far from won. Just as it was impossible to predict Oracle would come out on top in the database market, or that SAP would emerge as the leading BI vendor, there’s no telling which SQL and Hadoop providers will achieve dominance.
Watch the full interview for more exclusive insights, including more on in-memory analytics and the Big Data acquisition landscape.
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