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Dec 2020
... Gartner Research 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. ...
Analyst(s): Adam Ronthal | Rick Greenwald | Henry Cook
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Jan 2021
... Gartner Research 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. ...
Analyst(s): Henry Cook
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Feb 2021
... Gartner Research The logical data warehouse is now well established as a best practice for which there are many potential starting points and ways to expand. This research helps data and analytics leaders and their lead architects to ensure that their LDW projects are set up to succeed. Overview Introduction ...
Analyst(s): Henry Cook
... Gartner Research ...
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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
Mar 2021
... The Practical Logical Data Warehouse that was published in December 2020.
"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 ...
Analyst(s): Andrew White
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Dec 2020
... outcomes of AI. Overview Strategic Planning Assumption Introduction Analysis Gartner Recommended Reading Note 1: Logical Data Warehouse and Operationalizing AI Models ...
Analyst(s): Robert Thanaraj | Erick Brethenoux
... Gartner Research ...
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
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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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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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
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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
May 2017
... recently had the opportunity to write about the Logical Data Warehouse(LDW). In the paper I describe three parallel streams rather than a single development path. The development is cyclic. Like the classic data warehouse before it, the logical data warehouse is never finished. That is because it provides ...
Analyst(s): Henry Cook
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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
... selection
dbPaaS and cloud practices and technology
Logical data warehouse
Data management solutions for analytics Cloud Computing|Data and Analytics Leaders|Data Management Solutions|Data and Analytics Strategies B.A., Ethics, Politics and Economics, Yale University IBM|Senior Technical Marketing Analyst|4 ...
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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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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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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
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