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The Connection Between Good Data Management and Enterprise Agility

Dataversity

The word “agile” is defined in one dictionary as “quick and well-coordinated in movement; lithe.” The post The Connection Between Good Data Management and Enterprise Agility appeared first on DATAVERSITY. Click to learn more about author Russ Ernst.

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How Can Your Organization Implement the Right Test Data Management (TDM) Strategy?

Dataversity

The enormous amount of data in circulation has allowed enterprises to automate, advance, or accelerate business development with the help of agile methodologies. Thus, it is crucial to manage and streamline quality test data.

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Why the Next Generation of Data Management Begins with Data Fabrics

Dataversity

Agility is key to success here. However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY.

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The End of Agile – Part 3 (What Is Agile Really?)

The Data Administration Newsletter

In the first article, I laid out the basic premise for this series: an examination of how Agile has gone from the darling of the application development community to a virtual pariah that nobody wants to be associated with, and an exploration of the very important question of what we should replace it with. We […]

Agile 98
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Project Management for Aspiring Data Managers: Understanding Project Charters and Scopes

Analysts Corner

Why are they important for data managers? Undеrstanding projеct chartеrs and scopеs is crucial for data managers, rеgardlеss of thеir еxpеriеncе lеvеl. Communicatе еffеctivеly with stakеholdеrs: Data managers can clеarly еxplain data-rеlatеd aspеcts of thе projеct to stakеholdеrs and address any concerns or quеstions.

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How is the ‘Mesh’ Resolving Bottlenecks of Data Management

Smart Data Collective

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This is also true that decentralized data management is not new.

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The End of Agile – Part 4 (Lessons from Agile)

The Data Administration Newsletter

In my first article, I laid out the basic premise for this series: an examination of how Agile has gone from the darling of the application development community to a virtual pariah that nobody wants to be associated with, and an exploration of the very important question of what we should replace it with. We […]

Agile 52