First In-Memory Analytics and Now Natural Analytics to Disrupt BI from QlikTech

A recent article written by Cindi Howson in InformationWeek takes a look and a Business Intelligence (BI) and analytics provider’s success, but also writes about how they are not resting on their laurels. Howson writes about how QlikTech disrupted the BI market three years ago with QlikView and its in-memory analytics solutions.  QlikView’s in-memory analytics essentially allows one to query data when it resides in a computer’s random access memory (RAM), as opposed to querying data that is stored on physical disks.  This results in vastly shortened query response times, allowing business intelligence (BI) and analytic applications to support faster business decisions.

At the time of their IPO three years ago apparently some though that they would not be able to tread water amongst the Microsofts, SAPs and Oracles or the world. Well it seems as the naysayers were wrong with QlikView adoption rates still on the rise (Howson reports 24% in the first half of 2013) and those industry giants hopping on the in-memory train as well. So what is the secret to their success? Howson writes that, “QlikView’s in-memory engine has been part of its success, but more important has been its agile deployment capabilities and robust analytics. With the frenetic pace of business, agility now trumps a perfectly architected, broad BI solution — the strengths that incumbent BI platform vendors usually tout.”

There are differentiators and benefits to QlikViews in-memory approach such as associative search capabilities, dashboard and data-mart capabilities and ease of search compared to SQL but as we stated earlier, QlikTech is not settling. Howson writes that Natural Analytics is “QlikTech’s next attempt to disrupt BI. It’s a design approach that forces BI to work the way people discover and analyze data, says Donald Farmer, QlikTech’s vice president of product management. The three main ingredients of natural analytics include QlikView’s associative in-memory engine, a user interface that supports workflow and collaborative capabilities that let users explore data together.”