Remove Business Analyst Remove Data Validation 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 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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Data Analyst Interview Questions to prepare for in 2023

ProjectPro

Common Misspelling and Duplicate entries are a common data quality problem that most of the data analysts face. Having different value representations and misclassified data. 8) What are the important steps in data validation process? Involves analysing raw data from existing datasets.