Follow Datanami:
March 2, 2023

Data Fabric Maturation Means More Shrinkwrap, Fewer Consultants


Data fabrics today are primarily something that you or your consultant builds, not something that you can buy. But as data fabric solutions mature, the need to manually stitch various data management tools together will decline, and data fabric services will just work in the background on the cloud, says Forrester Principal Analyst Noel Yuhanna.

According to Forrester’s latest research, 65% of all data fabric deployments as of 2022 are performed by consulting services and system integrators such as Accenture, BearingPoint, Deloitte, Capgemini, Cognizant, Wipro, and Exela, Yuhanna says. Skilled (and highly paid) consultants do the hard work of making your ETL tool work with your governance tool work with your security tool, etc.

The good news is that the number of custom-built data fabrics has been on the decline. Five years ago, a full 82% of data fabric deployments relied on consultants to manually stitch the point solutions into a cohesive fabric, Yuhanna says.

“Give it another five years, that number will be like 40%, maybe,” the Forrester analyst tells Datanami in a recent interview. “I think the reason for the decline is the automation and intelligence coming to the platform. Eventually, this will go down to a single digit. Who knows–in a decade, the platform itself [may be] so intelligence that you don’t need anything. It drives by itself. Or maybe five years depending on how innovation happens.”

More intelligence and greater automation are hallmarks of what Forrester has dubbed data fabric 2.0 (see “Forrester Shares the 411 on Data Fabric 2.0” for more on Yuhanna and company’s latest research). The use of graph engines and enhanced real-time connectivity in data fabric offerings, among other capabilities, are enabling enterprises to get more value out of their data fabric investments.


While data fabrics today are typically built and not bought, that’s changing. Vendors such as Informatica, SAP, TIBCO, Oracle, Talend, and IBM (which Forrester mentioned in its latest report) are consolidating the various data management functions that traditionally go into a data fabric solution and offering more shrinkwrapped data fabric offerings, Yuhanna says.

“Traditionally they’re very isolated products,” says Yuhanna, who has been instrumental in defining the data fabric space. “If you look at IBM, they have tens or hundreds of products. But now they’re putting together this cohesive set of solutions [called Cloud Pak for Data]. And that’s what all the vendors are doing.”

That trend will continue, Yuhanna says. Asked to look into his crystal ball, the Forrester analyst sees clouds looming in data fabric’s future.

“Most of these [vendors], as they move to cloud they’re realizing they can have a solution set which can incorporate all these things tougher in a single solution from consumption perspective but also from an integration perspective, so that SIs are not going to be required to integrate those onsite with their customer, which is what’s being done today in most of these environments,” he says.

These are still very early days for something called data fabric as a service (DFaaS), but Yuhanna sees that as a trend. It’s possible you might not even know that you’re consuming a DFaaS when consuming other data management services in the cloud, he says. It’ll just work.

“Eventually it will be more like service-driven approach, where you just sign on and start to use fabrics,” he says. “You put in your credentials, you’re up and running, and you’re good to go. You don’t have to install and configure data quality separately from data modeling and security and governance.”

Considering the pain that many enterprises experience with data management as a task, and the various disparate tools that we use to automate data management to the extent it’s possible today, that’s very good news.

Related Items:

Forrester Shares the 411 on Data Fabric 2.0

Data Mesh Vs. Data Fabric: Understanding the Differences

Data Fabric Brings Data Together for Timely Decisions