Is a Data Fabric Still the Path to Frictionless Data Access?

Two and a half years ago, in mid-2021, I wrote a blog about data fabrics as a path of frictionless data access, a data fabric’s business relevance, and the technical barriers constraining a data fabric’s implementation.

By data fabric, I mean a modern distributed data architecture that includes shared data assets and optimized data fabric pipelines that you can use to address today’s data challenges in a unified way.

By frictionless data access, I mean

• Data for All Users and Use Cases: Provides timely, consistent, and trusted data for your wide range of analytic, operational, and governance use cases, as well as business self-service users.

• Data from Any Sources: Accesses, combines, and transforms both in-motion and at-rest data from across your diverse, distributed data landscape using metadata, models, and pipelines.

• Data that Spans Any Environment: Flexibly spans your distributed on-premises, hybrid, and multi-cloud environments.

Making the Case

In support of my point of view, I provided some industry facts on the problem along with a link to a white paper  Data Fabrics for Frictionless Data Access, A Technical Whitepaper by my good friend Rick van der Lans,

In this paper, Rick outlines the recipe for building a successful data fabric using a service-oriented approach and proven data management tools, including data virtualization servers, metadata management systems, master data management systems, and complex event processors.

Rick also describes in detail how these high-level tools provide the twelve key capabilities you need for frictionless data access, including:

• Data preparation, such as transformations, aggregations, filters, and joins

• Adaptable logic

• High performance

• Data access by many data consumption forms

• Access to all the data sources

• Processing of all types of data

• Data security and privacy

• Real-time data access

• Read and write data access

• Data minimization

• Event processing

• Technical and business metadata management

• Master and reference data management

More Insights on Data Fabrics

In the meantime, other experts wrote about data fabrics.  I found these two articles incredibly enlightening:

• Critical Components for Data Fabric Success by Alberto Pan at Denodo

•  Data Fabric Architecture is Key to Modernizing Data Management and Integration by Ashutosh Gupta at Gartner

Are Data Fabrics the Right Solution in 2024?

It is now two and a half years later. Thus, this is an excellent time to evaluate whether I was right in proposing a data fabric solution to the frictionless data access problem.

Are data fabrics the answer? Or are there other possible solutions that organizations should consider?

What do you think?

Insight Jam members would enjoy the conversation.