Takeaways from Gartner's Data & Analytics Summit 2018
I recently had the opportunity to participate in the Gartner Data & Analytics Summit 2018 in Dallas and noticed how drastically this conference has changed over the years. It used to be the Gartner MDM conference aimed at CIOs and MDM practitioners. This year’s theme, participants, and focus revolved around CDOs, CIOs, and enabling decisions through analytics.
The problem facing businesses has evolved considerably. In stark contrast to the mountains of data available to us now, in the past, businesses commonly lacked enough reliable data to make clear, confident decisions. Data management used to be a highly-centralized function. Today, all parts of an organization strive to create, curate, and manage data, pushing the data management industry toward a more decentralized model.
For the most part, businesses think they need to manage their data, when in fact, they need to transform it. They want to mold their data into information that can deliver insights which enable timely decision-making. To be effective, these insights must be the result of analytics fuelled by trustworthy and reliable data. Gartner’s Data & Analytics conference demonstrates that key business stakeholders have accepted the importance of this “great data, great analytics” model and strive to transform their businesses accordingly. The transformation is evident: in the attendees, who are increasingly data scientists rather than data stewards; in the vendors, who help businesses generate insights rather than manage data; and in the speakers, who demonstrate how they are solving complex multi-domain problems using analytics rather than traditional data management best-practices. This is a great thing for the data industry.
Moving to Decentralization
Four years ago, I presented a perspective at this same conference asserting that data management would become more decentralized because data consumption was becoming more federated. It triggered a vigorous debate as this was counter to the traditional centralization philosophy of MDM. This year’s conference clearly demonstrated that data management has evolved into a business-user-friendly, multi-domain, federated model in most businesses, and the concept of a centralized homogenous MDM is slowly beginning to fade away. Interestingly, the vocabulary of the industry is also evolving to reflect this change. For something that used to be called the “MDM Conference,” the word MDM is conspicuously absent.
The industry is recognizing that without the data-analytics-insight approach, effective decision-making becomes impossible. Data and analytics are forever conjoined and, together, will drive the value propositions, products, and vocabulary of the industry.
Data, Digital Transformation, and the Human Element
The Gartner conference, of course, had a powerful undercurrent of digital transformation this year. As usual, we had differing opinions on where the industry will be in a few years, but I can confidently say that as important as data and analytics are in driving digital transformation, we should not lose sight of the human element of everything we do. The most salient and powerful presentation of the entire event was given by Frank Buytendijk on that very topic. A quote in his session captured the essence of this interdependence of people and technology: “People, businesses, and things are interdependent, relational, and connected, rather than self-sufficient and autonomous.” When we think of analytics and data to make decisions and drive digital transformation, we can’t overlook the human side, because business success is not just about data and technology, it’s about relationships. AI can accelerate business processes, help create new products, and increase efficiency, but the flip side is that people lose their jobs and communities are impacted. As we use data to do business, it is also important for us to use data to do good.
This made me realize that we as data and analytics practitioners – and Dun & Bradstreet as a company – cannot miss the opportunity or fall short of our responsibility to understand how, through data and analytics, we can achieve a holistic understanding of our business and human connections and thereby build stronger relationships. This is one of the great promises of digital transformation: becoming relationship-centric. And without concise, conscientious data and innovative, insightful analytics, we’ll miss the tremendous opportunities that digital transformation can offer: to transform for the greater good.