Gartner 2019 Data & Analytics Summit Recap: The Future of Data and Analytics
One of the best parts of working in data is that the industry is in constant motion. Data strategy and tactics, data tools and data team structure are in a state of constant evolution. Amid all those shifts, there are also issues of access, governance and security to stay on top of.
No matter what your role is in the data analysis process, there’s always something new to experiment with. To learn more about the future of this fascinating field, I attended Frank Buytendijk’s session titled “The Future of Data and Analytics: Tales and Trends From the Center to the Edge” at this year’s Gartner Data & Analytics Summit. Here are a few of the things I learned:
There are too many data trends to adopt them all
Data technology is accelerating really quickly in all directions and the result is a series of concurrent but not necessarily related trends. It’s not always valuable to identify a trend and latch onto it. For example, it’s easy to see AI as one of the popular trends, but unless you have data collection processes to amass the enormous library of data required to run those analyses, adopting an AI program won’t create any value for you. You’ll also need an appropriate governance structure, more advanced analysis tools, etc. As such, it’s important to be aware of the trend and invest an appropriate amount of resources, so if that trend becomes more of a reality, your company is ready. In general, the right way to approach these trends is to create a storyline for your company that lines up a couple of related trends in a linear, connective way. When the trends are aligned as a series of steps spanning strategy, organization, business domain, governance and technology, you know you’re on the right track.
Data & analytics is a highly connected, constantly evolving story
Since data is ideally connected to every part of the business, changes to data process will affect every part of the business. Buytendijk laid out the appropriate process to make wide-ranging data decisions, making sure to align every stakeholder and piece of technology along the way. His process starts with decision support, then advances to operations decision making, effects on the digital platform and then finally impact on the larger business and society. Overall, the important takeaway here is that the more connected your data gets, the broader your considerations need to be when making changes to your data process. Think about how any individual change will impact all of the tools in your process as well as the related internal and external stakeholders. No data decision is made in a vacuum, so think about the extensive range of potential impacts of any individual move.
Centralized, deliberate data replaced by distributed, emergent data
It used to be the case that data was collected and managed by a select group of people on specialized teams, but data is now moving to a point where it’s part of every team’s decision-making process. To complicate things further, automation and a new class of tools have exploded data creation to the point that just having data on its own is no longer valuable, it has to be connected to other data to be valuable. The smarter our data tools get, the more data teams will move away from descriptive or diagnostic data and toward predictive and prescriptive data. This will require a fundamental change in the way data teams create value and determine relevant business questions.
Tomorrow’s data teams will be agile and take a portfolio approach
In a field moving as fast as today’s data and analytics industry, the teams that win will be the ones that are capable of moving the fastest. For example, it’s far more valuable to be able to introduce a new data source quickly than to have a full inventory of existing data. As data moves from centralized to distributed, data teams need to be able to introduce external data to their analysis instantly. It’s also important for these teams to realize that more advanced data will make it less necessary to have a predetermined business case. The trend of emergent data will reduce the need for a company to create their own questions to ask data. A portfolio approach will become more valuable as team lean on advanced data tools to determine its own questions.
If my notes from this sessions help you and your team, be sure to check out my blog post from yesterday’s The State and Future of the Office of the CDO: Gartner 2018 Chief Data Officer Survey session.