Describe and Explain the Four Processes of Data Transformation

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The Answer is The four processes of data transformation are extraction, transformation, loading, and validation.

1. Extraction: This process involves extracting data from various sources such as databases, files, and applications. The data is collected and brought together in a centralized location for further processing.

2. Transformation: Once the data is extracted, it needs to be transformed into a format that is suitable for analysis and reporting. This process involves cleaning the data, removing duplicates, and standardizing formats. It may also involve applying business rules and calculations to the data.

3. Loading: After the data has been transformed, it needs to be loaded into a data warehouse or other storage system. This process involves moving the data from the extraction location to the destination, and ensuring that it is organized and accessible for analysis.

4. Validation: The final step in the data transformation process is validation. This involves checking the accuracy and completeness of the transformed data. It may involve running quality checks, verifying data integrity, and ensuring that the data meets the requirements of the end users.

Overall, the four processes of data transformation are essential for ensuring that data is accurate, consistent, and ready for analysis and reporting. By following these processes, organizations can make better-informed decisions and gain valuable insights from their data.

Describe and Explain the Four Processes of Data Transformation

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Describe and Explain the Four Processes of Data Transformation

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Correct Answer:
Answered by ExamLex AI