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The Data Warehouse is Dead, Long Live the Data Warehouse, Part I

Data Virtualization

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

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The Data Warehouse is Dead, Long Live the Data Warehouse, Part II

Data Virtualization

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP). It consists largely of the application of new cloud-based technology to the same requirements and constraints.

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5 Ways Data Engineers Can Support Data Governance

Alation

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. How can data engineers address these challenges directly?

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The Data Lakehouse Myth

Data Virtualization

Reading Time: 2 minutes The data lakehouse attempts to combine the best parts of the data warehouse with the best parts of data lakes while avoiding all of the problems inherent in both. However, the data lakehouse is not the last word in data.

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The Data Lakehouse Myth

Data Virtualization

Reading Time: 2 minutes The data lakehouse attempts to combine the best parts of the data warehouse with the best parts of data lakes while avoiding all of the problems inherent in both. However, the data lakehouse is not the last word in data.

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Are Data Lakehouses Secure and the Best of Both Worlds?

TDAN

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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Why optimize your warehouse with a data lakehouse strategy

IBM Big Data Hub

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.