Remove Data Validation Remove ETL Tools Remove Raw Data Remove Unstructured Data
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Moving Past ETL and ELT: Understanding the EtLT Approach

Ascend.io

For example, unlike traditional platforms with set schemas, data lakes adapt to frequently changing data structures at points where the data is loaded , accessed, and used. These fluid conditions require unstructured data environments that natively operate with constantly changing formats, data structures, and data semantics.

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What is ELT (Extract, Load, Transform)? A Beginner’s Guide [SQ]

Databand.ai

The Transform Phase During this phase, the data is prepared for analysis. This preparation can involve various operations such as cleaning, filtering, aggregating, and summarizing the data. The goal of the transformation is to convert the raw data into a format that’s easy to analyze and interpret.

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What is ETL Pipeline? Process, Considerations, and Examples

ProjectPro

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

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