Data & Analytics Trends Gartner Will Focus on in 2017

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Gartner Inc is a well-respected analyst firm that provides users (you) with insights to help you accomplish your business goals. Much of the value comes via their inquiry system, in which you can speak directly to analysts with extensive backgrounds in the area of your choosing. However, you can also glean incredible amounts of information just by reviewing their event agendas. Read on to uncover Gartner's view on the most important data and analytics efforts to focus on for 2017.

Why You Should Care

First, I must answer the question "Why do I care what Gartner is focusing on for their Data & Analytics Summit?". Gartner painstakingly builds their event agendas by analyzing things like: most popular inquiry topics, vendor activity, market predictions, and customer case studies. The results of this analysis boils down into a selection of tracks and topics that are most popular, important and challenging to Gartner's users. Basically, these are the things your company will be spending money on in the next 12-18 months (so you should probably know what they are, right?).


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Changing Data & Analytics Roles

Based on the sheer number of sessions that mention roles/organization, I think it is fair to say that Gartner is pushing us to re-think our information infrastructure and modernize our approach to data. As data has begun to enjoy classification as an asset, more and more users are opening their minds and hearts to leveraging it for their own needs. This is creating a need for accessibility to all the information in the enterprise, hiring a bunch of data stewards won't cut it. Many analyst firms are calling this "Data Citizenship". This need/desire for open access to data and information is the catalyst for data governance solutions that help enterprises understand what data assets exist, where they came from, who has used them, and what the value is. DATUM's Information Value Management® is one such solution, offering users a way to clearly discover, understand and use data for their individual needs (no spreadsheets or SharePoint sites required!).

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The Internet of Things

See ya later "big data", a new term has taken over the top spot... and for good reason. I like this Forbes article which describes why IoT is so valuable through examples:

"Say for example you are on your way to a meeting; your car could have access to your calendar and already know the best route to take. If the traffic is heavy your car might send a text to the other party notifying them that you will be late. What if your alarm clock wakes up you at 6 a.m. and then notifies your coffee maker to start brewing coffee for you? What if your office equipment knew when it was running low on supplies and automatically re-ordered more?  What if the wearable device you used in the workplace could tell you when and where you were most active and productive and shared that information with other devices that you used while working?"

IoT has huge potential, but it requires some serious prep work. According to Gartner, "through 2019, one-third of Internet of Things solutions will be abandoned before deployment due to information capabilities (security, privacy, integration, metadata) built on traditional design and implementation methodologies."

Information capabilities will be a critical success factor for IoT deployments, so ensure you've built a data governance framework that accounts for the unique confidentiality, Integrity, and availability of IoT data. Several sessions at the Data & Analytics Summit will shed some light on this.

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Analytics Governance

A relatively new, but quickly growing concept is around analytics governance and how it is coming together with traditional information governance. Andrew White, VP Distinguished Analyst at Gartner, recently described the difference in his blog: "At the data level (inbound to the analytic app) the rules set are called information governance and at the analytic level (outbound from the analytic app) the rules set are called analytic governance. The former is well known and documented and still hard to do. The latter is relatively new, needs to follow the same model as does information, and remains equally harder to do."

So, when planning your data and analytics efforts for 2017, don't forget to check a very important (and free) source - the Agenda for analyst summits.

View Gartner Data & Analytics Agenda