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Jul 2020
... Gartner Research Data and analytics leaders must ensure that their data science and data warehousing teams work together. These two disciplines are notably different, but there is some overlap and they are highly complementary when used together. The AI and LDW systems must be designed to work together ...
Analyst(s): Henry Cook
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Oct 2019
... Automation Automated Data Mapping Automated Data Profiling Automate Data Warehouse Testing Data Marts The Operational Data Store (ODS) Augmented Transactions — aka HTAP Data Hubs Cloud Data Warehouse Any Data, Anywhere, Any Language Workloads Move — Bring Engine to Data or Data to Engine Strengths Weaknesses ...
Analyst(s): Henry Cook
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Jun 2012
... Gartner Research The logical data warehouse is a clear demarcation between centralized repository approaches and managed data services for analytics. Gartner presents the major components of the LDW. Analysis Business Drivers Defining the Logical Data Warehouse Repository or No Repository, That is the ...
Analyst(s): Roxane Edjlali | Mark Beyer
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May 2013
... Gartner Research The logical data warehouse (the next-generation data warehouse) improves agility, enables innovation and responds more efficiently to changing business requirements. This Decision Point presents a systematic and practical way to choose an LDW implementation style for a given use case ...
Analyst(s): Mei Selvage
Jan 2018
... These data items should be readily to hand in our DW.
Integrated Collaborating Engines Not Competing Solutions
The modern logical data warehouse is an integration of multiple analytic engines. However, rather than seeing the LDW components: the physical enterprise data warehouse, the data lake, data ...
Analyst(s): Henry Cook
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May 2017
... Technical professionals implementing the logical data warehouse can maximize their effectiveness and the business benefit delivered by explicitly integrating three analytics development styles: the classic data warehouse, agile with data virtualization, and the data lake. Problem Statement Solution Path ...
Analyst(s): Henry Cook
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Apr 2018
... Gartner Research The evolving nature of data in 2018 is forcing data management solutions for analytics (DMSA) architectures to evolve too. Technical professionals should adopt the logical data warehouse as the modern, "next-gen" data warehouse that uses a multiengine approach to fulfill conflicting ...
Analyst(s): Henry Cook
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Feb 2013
... Gartner Research The logical data warehouse has already emerged among leading warehouse practitioners. Analytics leaders must therefore learn to embrace it or risk rising information management costs for analytics and reduced business value. Impacts Analysis Impacts and Recommendations By combining ...
Analyst(s): Mark Beyer | Roxane Edjlali
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Sep 2012
... Research The use of data federation/virtualization helps enable virtual views of an organization's data for supporting a logical data warehouse. While not a new technique, it presents pragmatic opportunities for use in LDWs with the ability to create abstracted interfaces to data. Key Challenges Analysis ...
Analyst(s): Eric Thoo | Ted Friedman
Feb 2018
... reminded me of a concept that comes up repeatedly in my calls and is worth passing on as it can be a big help.
The concept is: Designing a Logical Data Warehouse (LDW) design, is like Town Planning, not like designing a building. When looked at from this perspective the design of an LDW is much more ...
Analyst(s): Henry Cook
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Dec 2014
... Gartner Research Solution architects for analytics, data warehouse leads and information leaders need to evolve to the logical data warehouse, to meet the current demands for flexibility in data management solutions for analytics, or face obsolescence. Key Challenges Introduction Analysis Replace the ...
Analyst(s): Mark Beyer
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Jan 2019
... Gartner Research Artificial intelligence/machine learning and the domain of the multiengine architecture of the logical data warehouse are complementary. Technical professionals working in data and analytics can increase business benefit by architecting their systems to take advantage of this natural synergy ...
Analyst(s): Henry Cook
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Feb 2013
... Leading Data Warehouse Implementers Show a 30% Adoption Rate for Big Data Data Integration for Data Warehouses Being Adapted for Big Data The telecom, media and business/consumer services verticals are most likely to adapt their existing data integration infrastructure across all types of big data, so their ...
Analyst(s): Mark Beyer | Ted Friedman
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Mar 2018
... the logical data warehouse is gaining market traction and acceptance, but data and analytics leaders still struggle with practical implementations. We demonstrate a pragmatic approach to the LDW by leveraging the data management infrastructure model. Key Challenges Introduction Analysis Align Data Management ...
Analyst(s): Adam Ronthal | Roxane Edjlali
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Aug 2014
... analytics has accelerated the need for expertise among data warehouse practitioners in deploying a logical data warehouse Gartner Recommended Reading ...
Analyst(s): Mark Beyer
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Jul 2015
... Gartner Research Healthcare provider CIOs, CDOs, and other information leaders and architects should use this educational Toolkit to blueprint their next-generation analytics architecture. When to Use Downloadable Attachments Gartner Recommended Reading ...
Analyst(s): Laura Craft
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Aug 2020
... Climbing the Slope Social Analytics Outdoor Location Intelligence In-DBMS Analytics Predictive Analytics Text Analytics Entering the Plateau Logical Data Warehouse Data and Analytics Services Appendixes Hype Cycle Phases, Benefit Ratings and Maturity Levels Gartner Recommended Reading ...
Analyst(s): Jim Hare | Peter Krensky | Austin Kronz
Jan 2018
... modular architectures, and their relationship to the dynamics of innovation and commoditization. I wrote up notes on how his ideas applied to the Logical Data Warehouse(LDW). It wasn't obvious which paper I might put this in, then my friend and colleague Mei suggested it would make a good topic for a blog ...
Analyst(s): Henry Cook
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Oct 2015
... Comparing the ODS, Sandbox and Data Lake Strengths Weaknesses Guidance Beginner: Build a Sound Data Platform Intermediate: Evolve Traditional Data Warehousing Toward the LDW Advanced: Optimize the LDW to Support Digital Business The Details Gartner Recommended Reading ...
Analyst(s): Mei Selvage
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Sep 2014
... No. 3: Integrate Data Using a Toolbox Approach Design Principle No. 4: Process Data Using a Toolbox Approach Design Principle No. 5: Evolve Toward a Hybrid Cloud Architecture Design Principle No. 6: Apply the Separation-of-Concerns Principle Close Examination of a Popular Data Warehouse Definition Conclusion ...
Analyst(s): Mei Selvage