A Breakdown of Eckerson Group’s “Data Fabric: The Next Step in the Evolution of Data Architecture”

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For decades, enterprises have tried to achieve consistent and unified viewpoints of data and analytics with various architecture solutions but kept coming up short. In the 1990’s it was the strategy of data warehousing and twenty years later it was data lakes––however, in recent years a new era in enterprise data architecture has established dominance and priority across organizations. Keep reading for a breakdown of the emergence and impact of the agile data fabric evolution.

The Evolution of Enterprise Data Architecture 

Data fabric is not a product you install at one time; rather it’s a holistic, architectural evolution of the data management and integration tools you already have in place. The report, “Data Fabric: The Next Step in the Evolution of Data Architecture,” from data research and consulting firm, Eckerson Group, discusses the development of several enterprise data approaches in the evolution towards data fabric architecture. 

  1. Data Warehousing: Beginning in the 1990s, this solution is the master dataset that consolidates enterprise data into a centralized repository and stores data from all areas to support business requirements.
  2. Data Lakes: Emerging in the 2010s, this approach is a centralized repository that houses structured, semi-structured, and unstructured data in its native form, regardless of the data size or volume.
  3. Data Fabric: Using artificial intelligence and machine learning (AI/ML), this approach encompasses its predecessors to automate and provide a unified view of enterprise data regardless of where the data resides or its format.

The Definition of Data Fabric Architecture

Data fabric is not a single product to replace data warehousing and data lakes; instead, it consists of several integrated solutions that provide a more robust architecture for enterprises dealing with disparate data locations and formats and a rapidly growing data landscape. According to the Eckerson Group report, “Data fabric is an architectural approach that uses metadata, machine learning, and automation to weave together data of any format in any location and make it easy to find and use by people or systems. It unifies the separate functions of data management—integration, preparation, cataloging, security, and discovery—into a cohesive process through intelligent automation.” 

The five aforementioned data management functions are not new, but integrating them is. With an automated agile data fabric, managing, onboarding, and combining new and existing data sources is faster and more streamlined which helps enterprises keep up with growing data demand and reliance.

The Strengths and Solution: TIBCO’s Data Fabric Framework

As a whole, the automated and integrated data fabric framework and architecture approach increases the value of enterprise data by making insights accessible and reliable for data-driven decision makers. The three main benefits of building a data fabric in your organization, listed in Eckerson Group’s data fabric report are: 

  • Faster time to insight
  • Reduced data management workload
  • More effective data discovery

With enhanced AI/ML incorporated into your data management framework, many data frustrations and manual delays are removed completely and organizations are able to focus on using insights for data-driven decision making that completely changes how enterprises do business.

At TIBCO, we help enterprises unify their data with an agile, modern architecture and eliminate the challenge of constantly keeping up with what’s best for business. With our easy-to-deploy data architecture that fits your complex, ever-changing use cases and technology landscape, your data fabric strategy will be optimized and integrated so you can intelligently simplify, automate, and accelerate your data pipelines.

Next Step in Deploying a Data Fabric

We understand that an agile data fabric needs a comprehensive list of solutions to thrive efficiently and effectively in your organization. Data Fabric is not a product you install at one time; rather it’s an architectural evolution. We do not advocate a rip-and-replace approach to your current architecture, but instead unify the data management and integration tools you already have in place. For more information on how we can ensure your data fabric architecture helps your enterprise evolve, contact our experts to get started.

Read the full Eckerson Group report, “Data Fabric: The Next Step in the Evolution of Data Architecture.”