What is the difference between Data ingestion and ETL?

Data Science, AI and ML
#1

Data Ingestion: Data ingestion is the process of connecting a wide range of data structures to where they need to be in the format and quality that they demand. It’s a process of repeatedly obtaining data from sources that aren’t usually linked with the target application, then mapping and arranging the foreign data into an internally approved format. This might be a storage device or a program that will be used for additional processing.

Data ingestion involves getting data into any systems that require data in a specific shape or format for downstream operational usage.

ETL: ETL stands for extract, transform, and load, and it is a technique for preparing data for long-term storage in data warehouses or data lake architectures. It is used to arrange and combine data from recognized, pre-planned sources into one of several well-known data structures for typical business intelligence and reporting.

The goal of ETL is to transform data into well-defined “stiff” structures that are ideal for analytics.

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#2

In SQL which one clause first works
Select
From
Where
Like
Order by
Group By

Write sequential operations

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