Extract-Transform-Load (ETL) architectural pattern
Description: The Extract-Transform-Load (ETL) design pattern is crucial for data integration and data warehousing processes. It involves extracting data from various sources, transforming it to fit operational needs, and loading it into a target database or data warehouse. This pattern ensures that data is accurately consolidated and structured for analysis and reporting purposes.
Main Elements of the ETL Design Pattern:
- Extract: Retrieve data from different sources, which can include databases, APIs, flat files, etc.
- Transform: Cleanse, format, and structure the extracted data to meet the required specifications. This might involve data validation, normalization, aggregation, and other data transformation techniques.
- Load: Insert the transformed data into a target system, such as a database or data warehouse, ensuring it is ready for use in analysis and reporting.
References:
Acceptance Criteria:
- Implement a basic ETL framework that includes modules for data extraction, transformation, and loading.
- Provide examples demonstrating how to use the ETL framework with different data sources and targets.
- Ensure the implementation follows the project’s coding standards and includes comprehensive documentation and unit tests.
https://upload.wikimedia.org/wikipedia/commons/d/d8/ETL_Architecture_Pattern.jpg @iluwatar is not found. Also, I would like to work on it.
Assigned to you @natashasrivastava. Sorry about the link that has stopped working, but I'm sure you can find plenty more references by searching for ETL pattern
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I will take care of it.
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Updated task description