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Demystifying Modern Data Platforms

Cloudera

A key area of focus for the symposium this year was the design and deployment of modern data platforms. Mark: The first element in the process is the link between the source data and the entry point into the data platform. The data products are packaged around the business needs and in support of the business use cases.

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What is Data Transformation?

Grouparoo

The difference here is that warehoused data is in its raw form, with the transformation only performed on-demand following information access. Another benefit is that this approach supports optimizing the data transforming processes all analytical processing evolves. Add geolocational information to support processing.

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What Data Engineers Think About - Variety, Volume, Velocity and Real-Time Analytics

Rockset

Variety One of the biggest advancements in recent years in regards to data platforms is the ability to extract data from storage silos and into a data lake. This obviously introduces a number of problems for businesses who want to make sense of this data because it’s now arriving in a variety of formats and speeds.

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What is Data Hub: Purpose, Architecture Patterns, and Existing Solutions Overview

AltexSoft

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

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Top 8 Data Engineering Books [Beginners to Advanced]

Knowledge Hut

The practice of designing, building, and maintaining the infrastructure and systems required to collect, process, store, and deliver data to various organizational stakeholders is known as data engineering. You can pace your learning by joining data engineering courses such as the Bootcamp Data Engineer.

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SQL for Data Engineering: Success Blueprint for Data Engineers

ProjectPro

Your SQL skills as a data engineer are crucial for data modeling and analytics tasks. Making data accessible for querying is a common task for data engineers. Collecting the raw data, cleaning it, modeling it, and letting their end users access the clean data are all part of this process.

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100+ Big Data Interview Questions and Answers 2023

ProjectPro

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.