ProjectPro
FEBRUARY 8, 2023
Data Integration and Transformation, A good understanding of various data integration and transformation techniques, like normalization, data cleansing, data validation, and data mapping, is necessary to become an ETL developer. Extract, transform, and load data into a target system.
Databand.ai
AUGUST 30, 2023
These tools play a vital role in data preparation, which involves cleaning, transforming and enriching raw data before it can be used for analysis or machine learning models. There are several types of data testing tools. This is part of a series of articles about data quality.
Databand.ai
JULY 19, 2023
However, ETL can be a better choice in scenarios where data quality and consistency are paramount, as the transformation process can include rigorous data cleaning and validation steps. Since ELT involves storing raw data, it is essential to ensure that the data is of high quality and consistent.
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