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An Introduction ETL DATA TRANSFORMATIONStoTABLE OF CONTENTS Introduction3Staging4 Transformations5Denormalization5Increasing Redundancy5Finding Balance7Calculations7Vertical7Horizontal8Internationalization9Language
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ETL data refers to the process of Extracting, Transforming, and Loading data from various sources into a centralized data repository for analysis and reporting.
Organizations that handle large volumes of data and need to integrate various data sources for business intelligence and reporting purposes are required to file ETL data.
To fill out ETL data, organizations need to extract data from source systems, transform it according to business rules or required formats, and then load it into a target database or data warehouse.
The purpose of ETL data is to combine data from multiple sources, clean and transform it, and load it into a warehouse or database where it can be analyzed to support decision-making.
The information that must be reported on ETL data varies based on the organization’s requirements but typically includes source data details, transformed data formats, and any applied business rules.
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