Knowledge Hut

DECEMBER 21, 2023

What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses. The purpose of data engineering is to analyze data and make decisions easier.

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Data Engineering Data Engineer Engineering MongoDB 52

Data Engineering Podcast

JUNE 11, 2021

Summary Google pioneered an impressive number of the architectural underpinnings of the broader big data ecosystem. In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. No more scripts, just SQL.

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Google Cloud Cloud Big Data Ecosystem BI 100

Edureka

JUNE 1, 2023

Without spending a lot of money on hardware, it is possible to acquire virtual machines and install software to manage data replication, distributed file systems, and entire big data ecosystems. This happens often in data analytics since running reports on huge data processes is done once in a while.

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AWS Data Analytics Cloud Amazon Web Services 52

phData: Data Engineering

JANUARY 3, 2022

With that in place, data engineers can build data pipelines to allow data to flow out of the source systems. The result of this data pipeline is then stored in a separate location — generally in a highly available format for various business intelligence tools to query. Data must also be performant.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Governance 52