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Data Virtualization: Process, Components, Benefits, and Available Tools

AltexSoft

In simple terms, data remains in original sources while users can access and analyze it virtually via special middleware. Before we get into more detail, let’s determine how data virtualization is different from another, more common data integration technique — data consolidation. Popular data virtualization tools.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

A pipeline may include filtering, normalizing, and data consolidation to provide desired data. In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The transformed data is then placed into the destination data warehouse or data lake.

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Data Science Course Syllabus and Subjects in 2024

Knowledge Hut

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Importance: Efficient organization and retrieval of data.