Today’s businesses collect more data than ever before, but many don’t have the architecture in place to store, process, and recall the data in real time. Whether an enterprise-level organization stores all its data in a single data lake or relies on multiple, disparate sources, both options cause significant delays in finding the specific information you’re looking for. Traditionally, if your organization wanted to update and upgrade the existing architecture, the only option was extract, transfer, and load (ETL) the data to a new framework but implementing a logical data fabric offers a better alternative — giving companies a cost-effective, efficient way to collect and integrate data while building a stronger framework across the organization.
At a recent CDO Data Summit, Mark Johnson, Fusion Alliance Executive Vice President and editorial board chair for CDO magazine, sat down with thought leaders in the data industry to discuss why logical data fabric is essential in accelerating time to value.
What is a logical data fabric?
When you have multiple disparate data sources, a data fabric acts like a net cast over the top, pulling individual information sets together in an end-to-end solution. Data fabric is a technology-driven framework that lies within the existing architecture, unlike a data mesh, which is a methodology regarding how data should be distributed among data owners and consumers.
In a logical data fabric, multiple technologies are implemented to catalog and organize existing data and integrate new data into the fabric. Data virtualization is the central technology deployed within this framework, creating an abstracted layer of unified data that is more secure and easily accessible.
What challenges are solved by a data fabric architecture?
Logical data fabric architecture offers a solution to the challenges organizations relying on numerous data storage solutions or repositories of structured and unstructured data face:
Overcome slow data delivery
By consolidating data into an integrated semantic layer, common business applications can process, analyze, and return the data in real time, in the language of the data consumer. This improves accessibility and significantly reduces latency that comes from applications having to search across multiple sources to return information.
If every data warehouse, database, and cloud-based platform within your organization relies on separate governance, you are dealing with significant inconsistencies. By stitching the data together in a logical data fabric, centralized governance can be applied across all data and automated to maintain and streamline the process.
Reduce IT bottlenecks
Data fabric automates how data is processed, integrated, governed, and utilized, enabling real-time analytics and reporting. This puts data in the hands of your BI and analytics teams more quickly while removing bottlenecks from your IT department. With a logical data fabric architecture, your business can respond to trends and changes within your industry more quickly, helping you to evolve both short and long-term strategies to reflect what your data is telling you in real time.
Is a logical data fabric the right solution for your organization?
Learn more about data fabric architecture from the CDO Data Summit’s round table discussion. Mark Johnson is joined by:
- Baz Khauti, President at Modak USA
- Richie Bachala, Principal, Data Engineering at Yugabyte
- Ravi Shankar, SVP and Chief Marketing Officer at Denodo
- Saj Patel, VP of Data Solutions at Fusion Alliance
This panel addresses critical questions about data in today’s business to help you solve your unique data challenges, including:
- Is the fabric of data virtual, physical, or both?
- How do we get value out of our data?
- Do we take a connect or collect approach?
- How comprehensive do we need our data approach to be?
- Are we optimizing for agility or for flexibility?
- How do we deliver unified data?
- Is the organization in agreement with what we are looking for out of their data?
- What AI/ML techniques do we want to employ, if any?
If you have specific questions or are ready to take the next step and learn how we can help you create custom data solutions for your organization, reach out to us today for a quick chat!
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