- ETL (Extract, Transform, Load) is a process in which data is extracted from source systems
- The testing of ETL refers to the process of accuracy and validating data
- Here are the eight steps involved in the evaluation process in this content
- Verifying business needs,Data sources need verification
- some of the best ETL testing tools
What is an ETL test?
ETL (Extract, Transform, Load) is a process in which data is extracted from source systems, and then based on business needs the data is converted and finally, the converted data is uploaded to the destination site. ETL processes play an important role in data-related projects such as MDM, Big Data, and Data Transfer.
The testing of ETL refers to the process of accuracy and validating data. This process can be preventing data loss and duplicate records. This test method ensures that the data transferred from the various sources to the central storage facility occurs in accordance with strict adherence to the rules of change and complies with all eligibility checks.
ETL Test Process:
The following are the eight steps involved in the evaluation process:
Verifying business needs: Assess reporting requirements, define the business flow, and design a data model based on customer expectations. The scope of the project should be clearly documented, interpreted, and understood by assessors.
Data sources need verification: Data quantity testing needs to be done to ensure that the column and table data types meet the specifications of the data model. Test keys must be in the correct location and duplicate data needs to be deleted. If done incorrectly, the combined report may be misleading or incorrect.
Get started designing test scenarios: define transition rules, create SQL scripts, and design ETL map shapes. The map document needs to be verified again, to ensure that it contains all the information.
Data extraction from source systems: ETL testing should be performed according to the needs of each business. Types of bugs and disabilities require identification experienced during testing. Errors need to be identified and resolved, bugs need to be fixed, and finally, the bug report will be closed before moving on to the next step.
Use flexibility: Make sure the data is converted so that the schema of the targeted data repository is properly aligned. Check alignment, data limit, and verify data flow. This map document is matched to the data type for each column and table.
Data needs to be loaded into the target storage: A record count needs to be done before and after the data is moved from the database to the database. Invalid data needs to be confirmed to be rejected and that default values are accepted.
Prepare in-depth report: Verify filters, options, layout and export performance report abridged. This report will inform participants and decision-makers of the results and details of the evaluation process.
The following are some of the best ETL testing tools:
Informatica Data Verification: This tool incorporates integration resources and power-based storage units. Allows analysts and developers to develop guidelines for mapping information. This tool provides data integrity solutions and full data validation. Information problems are visible and avoidable.
QualiDi: Everything in the test cycle is an automatic test with this tool. It allows customers to increase their ROI, reduce costs, and speed up market time. Based on the requirements, data tracking is provided on the targeted website. Fast and efficient project delivery and support are supported.
QuerySurge: Advanced RTTS solution for ETL testing. Designed for automated large data testing and data storage. Data management and data management are improved by this tool. Data transfer cycles are performed at a faster rate. This tool can provide testing on various platforms such as IBM, Teradata, Oracle, Amazon, and Cloudera.
SSISTester: Supervising experimental performance enabled the SSISTester UI in real-time mode. Testing can be done easily as it provides an accurate way to access packages, web resources, etc. This tool has a built-in project template. Test parameters similar to test errors, currently performed tests are provided by SSISTester. Test results can be saved and sent easily.
Data Gaps ETL Validator: This is a data storage tool. Project evaluation is simplified in the database, data transfer, and data integration. Millions of documents can be compared to the embedded ETL engine in this tool.
Conclusion: Organizations in order to perform sound business analysis collect data from multiple sources. Popular Business Intelligence (BI) tools can be used to process large amounts of data, in order to obtain important business information. In order to perform this process carefully, and ETL test (Extract, Transform, Load) is required.If you are looking forward to more in-depth ETL testing with a real-time view of the Computer Technology Articles industry, contact a leading software testing services company that will provide you with in-depth strategic solutions.