Analyst predictions: The future of data management
In the 2010s, organizations became keenly aware that data would become the critical ingredient in driving competitive advantage, differentiation and growth. But to this day, putting data to work remains a difficult challenge for many if not most organizations.
As the cloud matures, it has become a game changer for data practitioners by making cheap storage and massive processing power readily accessible. We’ve also seen better tooling in the form of data workflows, streaming, machine intelligence and artificial intelligence, developer tools, security, observability, automation, new databases and the like. These innovations accelerate data proficiency but at the same time add complexity for practitioners. Data lakes, data hubs, data warehouses, data marts, data fabrics, data meshes, data catalogs and data oceans are forming, evolving and exploding onto the scene.
In an effort to bring perspective to this sea of optionality, we’ve brought together some of the brightest minds in the data analyst community to discuss how data management is morphing and what practitioners should expect in 2022 and beyond.
In this Breaking Analysis, we’ll review the predictions from six of the best analysts in data and data management who will present and discuss their top predictions and trends for 2022 and the first half of this decade.
These experienced analysts include: Sanjeev Mohan, former Gartner analyst and principal at SanjMo; Tony Baer of dbInsight; Carl Olofso, research vice president with IDC; Dave Menninger, senior vice president and research director at Ventana Research; Brad Shimmin, chief analyst for AI platforms, analytics and data management at Omdia; and Doug Henschen, vice president and principal analyst at Constellation Research.
Prediction No. 1: Data governance becomes mainstream table stakes
According to Sanjeev Mohan:
I believe that data governance is now not only going to be mainstream, it’s going to be table stakes. And all the things that you mentioned, the data, ocean, data lake, lake houses, data fabric, meshes, the common glue is metadata. If we don’t understand what data we have and we are governing it, there is no way we can manage it. So we saw Informatica went public last year after a hiatus of six years. I’m predicting that this year we see some more companies go public. My bet is on Collibra, most likely, and maybe Alation.
I’m also predicting that the scope of data governance is going to expand beyond just data. It’s not just data and reports. We are going to see more transformations like Spark, Python even Air Flow. We’re going to see more streaming data. Kafka Schema Registry, for example. We will see AI models become part of this whole governance suite.
The governance suite is going to be very comprehensive with detailed lineage, impact analysis, and then even expand into data quality. We’ve already seen that happen with some of the tools where companies are buying smaller firms and bringing in data quality monitoring and integrating it with metadata management, data catalogs, also data access governance.
So what we are going to see is that once the data governance platforms become the key entry point into these modern architectures, I’m predicting that the usage, the number of users of a data catalog is going to exceed that of a BI tool. That will take time but we already see that trajectory.
We opened up the prediction for comments and the following were noteworthy:
Doug Henschen, while generally agreeing with Sanjeev on the importance of governance, believes we’re still a ways off from mainstream. His opinion is that too few organizations practice good governance because it’s difficult and incentives are lacking. He did point out that ESG – environmental, social and governance – mandates may be a catalyst, as it has been in financial regulation.
