“Generating a lot of data is one thing,” says Leo Gergs, principal analyst at ABI Research. “Being able to analyze and prepare this data for large language models and AI algorithm training is another.

“Data fabrics hold immense promise in transforming operations through seamless integration, enhanced governance and automated data management,” explains Gergs. “To unlock their full potential, it’s imperative to address a spectrum of challenges spanning technology, governance, operations and organizational readiness.”

According to Gergs, integrating legacy systems, on-premise platforms and cloud-native systems into a cohesive data fabric is a major hurdle. “Vendors like Databricks, IBM and NetApp are developing platforms that unify these environments, enabling real-time data processing and seamless compatibility,” he points out.

“The ability to bridge diverse systems is critical to unlocking the true value of data fabrics,” claims Gergs. “Enterprises manage sensitive and regulated data that require strict compliance frameworks.”

Manufacturers need to enforce governance with automated lineage tracking, access control and encryption. However, traditional methods like manual ETL (extract, transform and load) and siloed systems hinder scalability. Several vendors are addressing these bottlenecks by automating workflows, enhancing real-time analytics and streamlining operations.

“[Manufacturers] are looking to data fabrics for faster, smarter and more efficient data handling,” says Gergs. “Balancing customization for unique enterprise needs with scalable solutions is essential. But, in all of this, the right balance between customization and standardization is critical for widespread adoption and long-term success.”