Gartner® has had a long history of analyzing the potential of a logical approach to data management. In 2020, in “The Practical Logical Data Warehouse,” Gartner begins by saying, “The logical data warehouse — a data consolidation and virtualization architecture of multiple analytic systems — is used by both user organizations and vendors. This research provides practical advice for data and analytics leaders planning data management solutions for analytics.”
The Logical Data Management Approach
In the context of data management, “logical” doesn’t mean “sensible” so much as the opposite of “physical” – the physical (mechanical) reality of where and how the data is stored. However, at Denodo, we believe that there is something sensible about decoupling logic from mechanics. The Denodo Platform, a logical data management solution, effectively decouples logic from mechanics using data virtualization, a technology that is purpose-built for this decoupling. Note that “virtualization” is a part of Gartner’s definition of logical data warehouse, above.
Since as far back as 2012, when Gartner published “Understanding the Logical Data Warehouse: The Emerging Practice,” I believe that the logical data warehouse architecture has been undergoing rigorous vetting both from an analytical perspective, within Gartner and other analysts, as well as though practical application at many organizations.
Logical Data Management, Today
Fast-forward to this past December, when Gartner published a research note entitled “How to Establish the Logical Data Warehouse for Data and Analytics Use Cases.” In this note, the first Gartner recommendation is “Use the logical data warehouse architecture because it remains a current best practice to handle complex and mixed workloads, and helps position itself for the lakehouse, when it matures.”
I believe this is telling; people are starting to realize that the data lakehouse architecture, which promises to meet all of today’s data needs, is actually missing a few key capabilities. Fortunately, these can easily be provided by a logical data management solution.
Consider this:
- Data sources are more distributed than ever, and not all data can be consolidated within a single data lakehouse. Some data will always remain separate, if only due to data privacy regulations and multi-cloud configurations, in which companies keep multiple cloud systems for different purposes.
- Technology is diversifying and changing more quickly. Innovations such as GenAI require large quantities of disparate data, not only the data stored within the lakehouse, to be delivered to a large language model (LLM), often in real time. Logical data management makes this possible. See Gartner® “Leverage the Logical Data Warehouse for Better AI Outcomes” for more information about logical data warehousing and AI.
- Data products require coordination and governance across distributed teams. With a logical data management strategy, data governance is never fragmented, even if the relevant data sources are in different geographical locations or cloud systems. Logical data management enables governance and security to be managed across disparate sources from a single point of control.
- Data democratization demands personalization, for richer data consumption and data sharing. Logical data management platforms enable a powerful semantic layer above all applicable applications and data sources, one that automatically translates data in multiple ways, personalized for each recipient in their individual journeys.
It’s only Logical
Now – even with the advent of data lakehouses and other powerful cloud platforms – is the time to leverage a logical approach to data management. In addition to the other benefits mentioned here, it can also work with any existing infrastructure without having to replace costly investments. Clearly, it’s the most logical approach to take. Get in touch with us to learn more. Nota bene: O’Reilly is coming out with a new book entitled Logical Data Management: An Essential Strategy for Transforming Your Business, and we’re happy to provide you with a free, early release preview.
Gartner, The Practical Logical Data Warehouse, 9 December 2020, by Henry Cook, Rick Greenwald, Adam Ronthal.
Gartner, Understanding the Logical Data Warehouse: The Emerging Practice, 21 June 2012, by Roxane Edjlali, Mark Beyer.
Gartner, How to Establish the Logical Data Warehouse for Data and Analytics Use Cases, 10 December 2024, By Masud Miraz, Henry Cook.
Gartner, Leverage the Logical Data Warehouse for Better AI Outcomes, 24 May 2024, By Henry Cook, Afraz Jaffri, Adam Ronthal.
GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
- It’s Only Logical - May 20, 2025
- Preparing for a Logical Data Management Solution - June 25, 2024