AltexSoft

JUNE 26, 2023

The ultimate goal of data integration is to gather all valuable information in one place, ensuring its integrity , quality, accessibility throughout the company, and readiness for BI, statistical data analysis, or machine learning. Read our articles on structured vs unstructured data and unstructured data to learn more.

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Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

NOVEMBER 23, 2021

To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization. This post is a perfect place to learn about this approach, its architecture components, differences, benefits, tools, and more. What is data virtualization?

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Silectis

JANUARY 3, 2021

This data engineering glossary is by no means exhaustive, but should provide some foundational context and information. Advanced Analytics The process of discovering deeper insights in data than typically enabled by most business intelligence (BI) tools. Big Data Large volumes of structured or unstructured data.

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Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

JANUARY 19, 2022

An Azure Data Engineer is a highly qualified expert responsible for integrating, transforming, and merging data from various structured and unstructured sources into a structure used to construct analytics solutions. Data engineers must thoroughly understand programming languages such as Python, Java, or Scala.

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Data Engineering Data Engineer Engineering Scala 52

ProjectPro

JULY 27, 2021

Below are some big data interview questions for data engineers based on the fundamental concepts of big data, such as data modeling, data analysis , data migration, data processing architecture, data storage, big data analytics, etc.

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Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

OCTOBER 8, 2021

They are applied to retrieve data from the source systems, perform transformations when necessary, and load it into a target system ( data mart , data warehouse, or data lake). So, why is data integration such a big deal? Connections to both data warehouses and data lakes are possible in any case.

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