Article Data Architecture Data Management Data Warehouse 
Dataversity
MARCH 21, 2022
While data lakes and data warehouses are both important Data Management tools, they serve very different purposes. If you’re trying to determine whether you need a data lake, a data warehouse, or possibly even both, you’ll want to understand the functionality of each tool and their differences.
Dataversity
MAY 23, 2022
This is due to several facts beginning with the limitations of legacy infrastructure, the massive amounts of structured and unstructured data that organizations were collecting, […]. The post The Evolution of Data Virtualization: From Data Integration to Data Management appeared first on DATAVERSITY.
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Dataversity
APRIL 5, 2021
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. Agility is key to success here.
Dataversity
DECEMBER 14, 2020
It was only a few years ago that BI and data experts excitedly claimed that petabytes of unstructured data could be brought under control with data pipelines and orderly, efficient data warehouses. But as big data continued to grow and the amount of stored information increased every […].
Tableau
FEBRUARY 14, 2022
Editor’s note: This article originally appeared in Forbes. Let’s look at a few focus areas of a people-centric strategy to help you achieve trusted data and successful AI projects: your data architecture, the processes for managing governed data, and balancing the roles of people and machines. Vidya Setlur.
Tableau
FEBRUARY 14, 2022
Editor’s note: This article originally appeared in Forbes. Let’s look at a few focus areas of a people-centric strategy to help you achieve trusted data and successful AI projects: your data architecture, the processes for managing governed data, and balancing the roles of people and machines. Vidya Setlur.
The Data Administration Newsletter
MAY 31, 2022
As we enter a new cloud-first era, advancements in technology have helped companies capture and capitalize on data as much as possible. Deciding between which cloud architecture to use has always been a debate between two options: data warehouses and data lakes.
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