Aligning Data Virtualization, Streaming, and ETL

Aligning Data Virtualization, Streaming, and ETL

What do data virtualization, streaming, and extract, transform, and load (ETL) processes have in common? They all deliver data from disparate sources to the business intelligence (BI), analytics, and other applications used by businesspeople, data scientists, and analysts. Like utilities,…

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Data Virtualization: Thinking Outside the Bowl

Data Virtualization: Thinking Outside the Bowl

Across all vertical markets, organizations adopt data virtualization as a core part of their IT infrastructure because data is becoming more distributed, more heterogeneous, and larger in volume. The pressures on business to be more competitive are continually growing, so…

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The Virtual Data Lake for a Data Scientist

In the previous article we reviewed the architectural elements of the virtual data lake, dug deeper into its technical implications. In this post, we will review the architectural elements of the virtual data lake, and will discuss why a virtual…

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The-Role-of-Data-Virtualisation-in-a-Data-Lake

The Role of Data Virtualisation in a Data Lake

It seems at present there is huge amount of hype on big data and the concept of a data lake. Already however there is confusion as to what a data lake is with multiple different definitions ranging from a centralised…

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Logical-Data-Warehouses-and-Why-They-Matter

Logical Data Warehouses and Why They Matter

Recently there has been a lot of discussion around the concept of the logical data warehouse. What is the cause of this buzz? Why are logical data warehouses so important for data professionals? To understand this, we first need to…

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