From Data Management to Data Fabric

October 26, 2022


The global volume of digital data production is growing at a breakneck pace. From 2020 to 2025, IDC forecasts new data creation to grow at an annual rate of 23%, resulting in approximately 175 ZB of data creation by 2025. 

While this relentless data growth can feel overwhelming due to its sheer volume, it can also create opportunities for corporations to gain better insights to run their business leveraging various modern data analysis techniques.  

As the data necessary to gain more business insights is scattered and siloed, an industry trend is to centralize it in a data lake and perform analytics there, which come with its fair share of challenges, such as storage costs, data governance, and data protection.

Hence the growing interest in the alternative concept of "data fabric", which Gartner identifies as a top strategic technology trend for 2022 and as the future of data management.

Your Data Integration Journey

Your business collects and stores data, and you are eager to extract insights from various sources of data to improve your bottom line, run your business better, serve your customers better, or simply to adjust your products to your target customers with better insight.  

Take a moment to make an honest self-assessment of where your company stands in terms of Data Integration today, and where you want to be tomorrow:

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  • Data-informed: The data you collect is readily available for decision-makers. Data is referenced to justify decisions, but decisions are largely driven by human intuition and experience.
  • Data-driven: Decisions largely depend on the data that is collected and stored in dedicated “big data“ systems, that is often pre-processed by tools and algorithms for consumption by decision-makers.
  • Data-centric: Data collection and ingestion is a prominent and permanent role in the organization's processes and decisions. Several teams are dedicated to data science across the organization.

 What’s the best way to gather Data Insights? 

To enable data analytics, most businesses tend to copy data from various sources to a data lake. With the help of products such as Splunk, data scientists can then transform and integrate large amounts of raw data that is stored in its original format and proceed to generate insights for the business.  

As we discussed in our previous article about Data Gravity, replicating data to a data lake can be concerning, in terms of: 

  • Storage and replication cost 
  • Data integrity 
  • Data security 

As British mathematician Clive Humby rightly stated, Data is the new Oil, but while extracting data, you do not need to get your hands dirty.

A more elegant way is to leverage the concepts of a Data Fabric, which can be conceptually understood as a single management layer on top of scattered, siloed data to orchestrate data access. IBM describes Data Fabric as a “holistic tapestry connecting information across disparate data storage systems''. This method removes the need to copy data, thus removing the complexity that is involved in Data Replication and Data Governance, while making all data available across an enterprise.

To assemble this tapestry using your existing siloed data into a Data Fabric, robust Data Management solutions are needed that are adapted to the data management system used.

The right data management products are instrumental to build a data fabric solution. 

To expose your siloed data storage systems to the Data Fabric layer, you need Data Management products, with 3 main characteristics: 

  • Ease of access to the tools and data (via REST-APIs): Modern open-source access 
  • Operational Efficiency: automation & metadata management capabilities 
  • Data protection and compliance 

Mainframe Data Management from Broadcom  

Broadcom offers a variety of solutions for Data Management. “We deliver leading solutions to house, organize, manage, report on, and archive mission-critical data” explains Deb Carbo, Director of Product Management. “We help our customers amplify their Mainframes value by turning #data into Insights with best-in-class Data Management Solutions”.

If you’d like to discuss this topic further, please contact