The ETL (Extract, Transform, Load) process is a fundamental component in data migration and data integration. It consists of three main phases: Extraction, Transformation, and Loading. Below is a description of the process steps of the ETL process:
1. Extraction
The first step in the ETL process is the extraction of data from source systems. This involves collecting relevant data from various sources such as databases, ERP systems, flat files, or cloud storage. Steps:
- Identification of data sources: Determine which systems and databases contain the required data.
- Data selection: Decide which specific data needs to be extracted. This can be based on criteria such as date, department, product line, etc.
- Choose extraction methods: Determine whether the extraction should be done in bulk or in real-time, depending on the organization’s needs.
- Perform extraction: Execute the actual data extraction and temporarily store the data in a staging area for further processing.
2. Transformation
In this phase, the extracted data is converted into a suitable format for the target system. Transformation includes a series of activities to ensure data quality and consistency. Steps:
- Data cleansing: Remove duplicates, correct errors, and fill in missing values. This applies to most data objects but can be optional for financial transactional data objects. Booking errors in the old system are often not eliminated in the transformation set but migrated to the new system (for accuracy and completeness).
- Data standardization: Convert data to a uniform structure and format, such as converting date notations or currencies. Data migration is an ideal time to apply data standardization and enrichment. It makes post-migration reconciliation more complex but provides more value for the company that will be working with the data.
- Data enrichment: Supplement data with additional information from other sources to increase usability.
- Data mapping: Define how fields from source systems are mapped to fields in the target system.
- Apply business rules: Implement specific transformations and calculations based on business logic.
3. Loading
The final step is loading the transformed data into the target system. Steps:
- Pre-validation of data: Check if the transformed data is correct and complete before loading.
- Initial Load: Perform the initial data load to the target system, often in bulk, to transfer the initial set of data. You can migrate on a net basis (e.g., a balance per general ledger/cost type/cost center/period/project line, or a combination of elements) or with the entire detailed dataset, depending on information needs and/or desired migration timeline.
- Incremental Load: Load new or updated data into the target system on a regular basis to keep the data up-to-date.
- Verify integrity: Ensure that the loaded data is correct and consistent within the target system.
- Performance tuning: Optimize load processes to ensure they are efficient and fast.
Summary
The ETL process is essential for successful data migration and ensures that data from various sources is collected, cleansed, transformed, and ultimately loaded into a new system. This process guarantees the integrity, accuracy, and consistency of the data, which is crucial for reliable reporting and decision-making.