What Is ETL Testing? Know All About It

Since various organizations have begun to use ETL to combine and relocate data, ETL testing needs to be carried out to confirm the authenticity of the process. However, ETL testing can prove difficult sometimes because of the sheer amount of data that it works with. Moreover, its diverse characteristics always make other aspects of ETL seem complex.

On the other hand, ETL testing means any data that has been relocated to the data warehouse will possibly be used for analysis and aspects of business logic. In this article, we’ll look at various aspects of ETL.

What Does ETL Stand for?

The term ETL is an abbreviation for Extract-Transform-Load. It’s all about the movement of data from the data source to the data destination.

What is ETL Testing?

ETL testing confirms that the data in the new system has been successfully extracted and transformed using the proper format. The purpose of the testing is to ensure no issues arise concerning the quality of the data while the ETL procedure is ongoing. One such issue includes data loss. Therefore, ETL testing is a way to confirm that there are no glitches or faults.

What is the Importance of ETL Testing?

Various businesses nowadays depend on data to function. It is very effective, especially when the data in question is correct. The data provides us with an excellent understanding that is better than what our thinking faculty can analyze. In the case of ETL testing, it makes it possible for your data to come out 100 percent without errors.

Eight Aspects of ETL Testing

1. Define Your Business Necessities

Define the target systems, data sources, and modifications needed

2. Confirm Your Source of Data

Carry out a counting procedure on your data source to ensure the whole data was migrated successfully.

3. Structure Your Test Cases

Test targets system data for authenticity and completion. You can also try performance testing.

4. Begin Data Extraction from the Source System

Begin your data extractions from the source system and ensure the process was wholly carried out.

5. Use Data Transformative Techniques

Make sure the data is completely transformed to the file format that suits the target systems.

6. Move the Data into the Target Warehouse

It is one of the key benefits of ETL testing. You use record count to confirm the complete movement of data to ensure the data isn’t rejected.

7. Create a Summary of Your Findings

Create a summary report of all your findings during the process.

8. Testing Conclusions

Bring the testing to an end.

Nine Types of ETL Testing

The following are the nine types of ETL testing:

  • ETL validation testing
  • Count from data source to target destination testing
  • Data source to target data testing
  • Metadata testing
  • Efficiency testing
  • Data authenticity testing
  • Data combination testing
  • Summary report testing
  • ETL regression testing

Other testing procedures also include GUI testing and user acceptance testing.

ETL Testing Challenges

ETL testing challenges are unavoidable because of the massive data involved in the process. Since the usual software testing strictly involves coding, ETL testing is complex because the whole process involves data. Here are some of the challenges:

  • Loss of data during transmission
  • Shortage of source data
  • Incomplete data transmission requirements
  • Incomplete data
  • The large volume of data makes the testing difficult
  • Use of inferior ETL testing tools

Things to Consider to Find the Best ETL Testing tools

When you plan on getting an ETL testing tool, you should consider the following:

  • Go for an ETL testing tool with a graphical interface
  • Go for one that has an automated code generator
  • Go for an ETL tool that has a built-in data connector
  • Go for an ETL tool with content management feature
  • Go for one with a superior debugging tool feature

How ETL Testing Can Influence the Future: Cloud and AI

Using hand-coded scripts is not enough to increase your company’s productivity. When using ETL tools, you can process massive amounts of data without any human assistance. With this possibility, Cloud and AI now have data integration support which is fast becoming a new trend. DataQ’s ETL testing tool will help you improve the quality of your data by automating manual testing.

Conclusion

ETL testing is a vital part of the data quality checks for any company. It ensures that your data will be in good shape and ready to use when you need it. DataQ ETL testing services can help you get the data quality automation your business needs. Contact us today to learn more about our products and solutions. We want to ensure that all customers have access to high-quality tested data for their analytics projects, regardless of size!