What is the ETL testing process and tools? Computer Articles | September 16, 2021.

What is the ETL testing process and tools?
Computer Articles | September 16, 2021.

Organizations collect data from a variety of sources for meaningful business analysis. Popular Business Intelligence (BI) tools can be used to process large amounts of data, in order to gain valuable business insights. ETL (Extract, Transform, Load) testing is required to perform this process carefully. In this article, you will learn about the ETL testing process and the various ETL tools.

 

What is the ETL test?

ETL (Extract, Transform, Load) is a process where data is extracted from the source system, then the data is converted based on business needs and finally, the converted data is loaded into the destination database. Goes Goose ETL processes play a key role in data-related projects such as MDM, big data and data migration.

ETL testing refers to the process of qualifying, verifying and correcting data while preventing data loss and duplicate records. This method of testing ensures that the data transferred to the central warehouse from various sources complies strictly with the rules of change and all accuracy is checked.

 

ETL testing process:

The eight steps involved in the testing process are as follows.

Identify business needs: Evaluate reporting needs, define business flow, and design data models based on client expectations. The scope of the project should be clearly understood through documentation, designation and evaluation.
Data source verification required: Data counts need to be checked and then verified that the column meets the data type and table data model features. Check keys should be in place and duplicate data needs to be removed. If done incorrectly, the overall report may be misleading or inaccurate.
Start designing testing cases: Explain the rules of change, create MySQL scripts, and design ETL mapping scenarios. The mapping document also needs to be corrected, to make sure it contains all the information.
Extracting data from the source system: ETL tests need to be tailored to business needs. The types of bugs and defects that appear during the test need to be identified. Errors need to be detected and corrected, bugs need to be corrected, and then the bug report needs to be closed before moving on to the next step.
Apply the logic of change: Make sure that the data has been changed so that the scheme of the target data warehouse matches the target exactly. Verify alignment, data range, and data flow. This ensures that the mapping document matches the data type in each column and table.
Data needs to be loaded into the target warehouse: Record counts need to be checked before and after the data is transferred from staging to the warehouse. Invalid data needs to be verified that it has been rejected and default values ​​have been accepted.
Prepare an in-depth report: Verify the functionality of the summary report’s filters, options, layout and export. The report will inform stakeholders and decision makers of the results and details of the screening process.

LET

Informatica Data Verification: This tool integrates integration services and repositories with the power center. It allows analysts and developers to develop guidelines for testing mapped information. This tool offers data integrity solutions and complete data validation. Information problems are identified and avoided.
QualiDi: Every element of the test cycle is automated testing by this tool. It allows consumers to increase their ROI, reduce costs and speed up market time.

QuerySurge: This is an RTTS developed solution for ETL testing. It is designed for big data testing and data storage automation. This tool improves data governance and data quality. The data transmission cycle is performed at high speed. This tool can provide testing on various platforms such as IBM, Teradata, Oracle, Amazon and Cloudera.
SSISTester: SSISTester’s UI allows monitoring of test execution in real time scenarios. The test can be easily implemented because it provides an intuitive way to access packages, database resources, etc. Test parameters such as test errors, currently available tests SSISTester provides. Test results can be easily saved and sent.
Data Gaps ETL Validator: This tool is for data warehousing. It’s easy to test data warehouse, data migration, and data integration plans. Millions of documents can be compared to the ETL engine included in this tool.
Corollary: If you’re looking for a better insight into ET.

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