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Democratizing Analytics: What Matters Most in Today’s Solutions

In our eyes, “Democratizing Analytics” means building and marketing technology that is (1) easy to use, (2) accessible, (3) full of actionable insights and (4) inexpensive. These four pillars, when united, will result in the expansive use of analytics across a wide variety of settings.

“Easy to use” is, apparently, a very elusive goal—even today. Despite aesthetic updates over the past few years, both established and recent entries into the analytics space are still (put simply) quite baffling. From day one, we knew that even the most revolutionary platform would only make a difference if it was geared for use by anyone and everyone.

For a product to be accessible, we mean that all users in an organization—from data scientists to product engineers and business analysts—should be able to quickly familiarize themselves with the software and enjoy its use. Simultaneously, this means that all software should permit not only individual access, but also group access.

This notion also requires that a product must be available for use through the platforms that customers use every day—especially mobile devices and tablets, such as the Apple iPad. This means not merely displaying data or dashboards, but allowing for data analytics and interactive visualizations that are truly available on-the-go.

Within this democratic movement, three groups of users are direct beneficiaries:

Group One: Business ExecutivesThis group is obviously composed of non-data scientists and non-analysts. They have depended on dashboards for years to deliver summarized information, but they increasingly desire deeper insights into their businesses. This need arises partially from pressure—competitors purporting to have the best analytics in the industry are frightening and must be met on equal ground—but also because of new business demands. One demand, in particular, is gleaning novel insights from an influx of social networking data to reveal “the voice of the customer” (as captured from Facebook, Twitter, blogs, websites, etc.).Group Two: Data and Business Analysts

This burgeoning user group is typically highly educated, technology and business savvy and (increasingly) tasked to conquer big data and analytics challenges. This group’s analytical needs, as examples, include: instrumenting applications for the corporate website and collecting data; understanding and analyzing various traditional business data relative to social; or creating data-driven apps to better understand mobile customers. Building accessible tools to deal with their data needs—especially interactive interfaces—is key. (It is also a necessary condition for underlying technologies, especially Hadoop, to achieve widespread adoption.)

Group Three: Data Scientists and Software Engineers

These “kings” of the big data and analytics mountain serve various constituencies from groups one and two who are demanding “more insights into their data with faster turnaround.” Data scientists and software engineers are trying to get the most out of their current tools (some big commercial solutions, some home-grown products and some open source projects) to be more productive. Their need for accessibility is two-fold: more data (partially an IT solution and partially a programming solution) and better tools.

Democratizing analytics does not begin and end with putting sophisticated statistical and mathematical software into the hands of scientists; instead, it’s an approach that aims to yield intuitive, easily interpreted resources for the decision makers that need them most. To get there, we’re focusing on superior user experiences, stronger analytics and significantly lower costs.

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