A Takeaway from the Forrester Data Strategy and Insights 2018 Event

Turning Powerful Visions into Reality

Chris ReedDecember 18, 2018

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“Are we there yet?”

If you have children, or were even just a child once, you’ve likely heard or spoken these words on a car ride somewhere. It’s an often annoying question, typically asked repeatedly by kids who are impatient to get to a destination.

The answer can vary, but it’s almost always some variation of, “no!”

The Forrester Data Strategy and Insights 2018 conference was filled with dynamic speakers and compelling content. It introduced what I’d even call some ground-breaking ideas for the future of data management and analytics. Yet in my mind, I kept hearing a variation of those words, made famous from countless road trips, over and over again:

We’re not there yet.

The event explored what the future may hold and how to get there, and while much of the content was inspirational, for most organizations it was also largely aspirational. For the Googles and Amazons of the world, the goals discussed may have seemed eminently attainable. After all, they’re the very definition of data-driven companies, shaped the age of big data, and ride the cutting edge of data innovation and advancement. But comparatively speaking, the vast majority of organizations’ data management efforts are still in their infancy.

Now, don’t misunderstand—when it comes to predicting where the data world is going and the best tools and path to get there, Forrester is at the forefront. But for some, the value of this conference was much like the value of attending an auto show, where you can view all the latest models, as well as the concept cars of the future. Reality is, many still have a lot of practical work to do in the data management trenches before we get to where Forrester envisions. A great number of organizations must still master the data management basics before they can make the visionary a reality.

Tackling Data Management Basics

To do this, most organizations must learn to walk before they can run. Everyone is intrigued with the possibilities of advanced analytics, but some companies are still battling to even get a data governance budget. Other organizations are plagued by widespread mistrust of their data. Many don’t know where to start or how to fix a haphazard enterprise data management strategy. For them, the potential of analytics is often a pipe dream.

But fear not. I’ve put together some basic first steps that must be taken before advanced analytics can become a reality:

  • Make sure your data consumers know where your data is and how to find it. A good data governance program will implement tools that can track the location of, and manage access for, your data assets, which is important from a compliance perspective (like the location of personal data). It is also important to have a facility to provide feedback on these data sets. The feedback will let users know if the data is “fit for purpose”. These capabilities are important because they let users know what’s available to choose the best assets to leverage for analysis.
  • Make sure business users know data and business term definitions. Data governance programs should maintain a glossary to ensure consistent enterprise-wide understanding of data assets and attributes, so the correct data is used for analytics.
  • Ensure data quality with rigorous checks such as data profiling, consistency, conformity, completeness, timeliness and reconciliations. Building trust in the quality of the data encourages business users to use data resources for analytics with confidence, increasing high value insights.
  • Monitor to sustain and improve data integrity across the data supply chain, so the data used for analytics doesn’t generate flawed and faulty results.
  • Establish a solid data management framework and implement a cohesive solution and strategy that includes data quality, governance, and analytics to generate the greatest value from data assets.

Chasing the Vision

Your data management strategy must ensure these basics of data quality and data governance before you prepare data sets for analysis, if you want the results of that analysis to be truly valuable. There are literally hundreds of data tools available to help you uncover business insights from within your data stores, but you need to be able to trust those insights. That level of reliability only comes with good governance and data quality.

An all-inclusive data intelligence platform that brings together data quality, data governance and analytics delivers both an integrated solution and empowers business users to help drive those analytics and insights. This helps to foster a data-driven culture, getting you closer to becoming an organization who derives real competitive power from their data, as Forrester envisions.

For more information on how our all-inclusive data intelligence platform can help both master the data management basics and achieve your long-term strategy and vision, download the data sheet below.

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