Sean R. Coombs

Ninety-five percent of organizations see impacts in their organization from poor data quality. This statistic is just one of many findings that our annual 2019 Global data management research report unearthed.

Digital transformation is the modern-day Gold Rush. To reach new markets and grow revenue, business leaders across industries are flocking to embrace new technology and digital processes. And it’s no wonder why! The digital economy offers a myriad of benefits to businesses and consumers alike. While consumers can expect mobile-optimized and personalized experiences, businesses will appreciate having better insight for decision-making and product innovation. However, digital transformation also brings its own set of challenges, from external regulatory hurdles to internal technology limitations.

Business leaders today are using data to power all sorts of initiatives, from uncovering revenue opportunities to complying with regulations. More and more, data is becoming a mission-critical asset that many argue should be tracked on a balance sheet. In fact, nearly all of the C-level executives in our 2018 global data management benchmark report (95%) believe that data is an integral part of forming their business strategy—a sentiment that has increased by 15 percent over the prior year.

Last week, I had the privilege of attending the 2018 MIT CDOIQ Symposium in Cambridge, Mass. The event brings together data practitioners and business leaders from a variety of sector to advance the professional development of Chief Data Officers. Throughout the three days of workshops and classroom-style lectures, attendees were treated to a rich agenda with topics ranging from regulation to artificial intelligence. While I wish I could have attended all of the sessions, I wanted to share some common themes from the workshops I did attend.

So you convinced your business leadership that investing in a data governance program is in the best interest of the company. Now what? While embarking on a data governance program is an exciting time for any enterprise data management team, it can also be a big undertaking. With little example to follow, those beginning a data governance program, and even those who have implemented one recently, would be wise to follow industry best practices and learn from some of the cautionary tales out there. Knowing what works, and what doesn’t will help you get your program stood up faster and with greater efficiency. Here are the data governance best practices that we saw throughout the 2018 Data Governance and Information Quality (DGIQ) conference: 

The presenter walks on stage in a dimly lit arena, stands beneath a bright, purple-hued spotlight, and delivers opening remarks using words like “artificial intelligence” and “predictive analytics.” Suddenly, the ears of more than 3,500 data professionals stand at attention, and the audience has a collective thought: “This is how we’re finally going to use our data to do something innovative.” Because that’s what the Gartner Data & Analytics Summit 2018 is all about: coming together to share experiences with our data programs, to tell stories of failure and of success, and to learn best practices from other experts in our field. In this post, I wanted to share my key takeaways with you, so you too can benefit from this collective experience.

Data is quickly becoming the currency of the digital economy. The organizations that are able to best leverage their data for strategic decisioning will be well-poised for success in the years ahead. Nearly all of the C-level executives in our study (95%) believe that data is an integral part of forming their business strategy—a sentiment that has grown by 15 percent over the prior year. 

Bright and early on a Thursday morning, hundreds of data professionals convened for the 2017 Data Governance Financial Services (DGFS) conference. Hosted in Jersey City, New Jersey, DGFS brings together likeminded and passionate data professionals from across the country with a common mission: to share best practices and overcome challenges related to their data governance programs.

An effective data management strategy is good for your business. As organizations today rely on their data to help drive business initiatives, the quality of that information is growing increasingly important. But you probably already knew that. It turns out that data professionals spend a lot of time talking about data in terms of its accuracy and a lot less time talking about its accessibility and readiness. While the importance of accurate data is undeniable, organizations should understand that having accurate data is only a benefit if you can access that information when it’s needed.

Businesses talk a great deal about being data-driven. Yet, using data for strategic purposes can often prove to be more challenging than it would first appear. Organizations today are at the center of a data dilemma, plagued by inaccurate and unstandardized data, information that is scattered across disparate systems, and a lack of defined processes and skilled employees. Yet, business users are demanding access to data with greater urgency than ever before.