Test cases, data, and validation procedures are crucial for data transformations, requiring an understanding of transformation requirements, scenarios, and specific techniques for accuracy and integrity. Data transformations require complex testing due to their sophisticated logic, computations, and dependency on real-time data streams. This necessitates extensive test case design, representative data, automation tools, and robust validation […]
It’s Essential – Verifying the Results of Data Transformations (Part 1)
Today’s data pipelines use transformations to convert raw data into meaningful insights. Yet, ensuring the accuracy and reliability of these transformations is no small feat – tools and methods to test the variety of data and transformation can be daunting. Transformations generally involve changing raw data that has been cleansed and validated for use by […]
Choosing Tools for Data Pipeline Test Automation (Part 2)
In part one of this blog post, we described why there are many challenges for developers of data pipeline testing tools (complexities of technologies, large variety of data structures and formats, and the need to support diverse CI/CD pipelines). More than 15 distinct categories of test tools that pipeline developers need were described. Part two delves […]
Choosing Tools for Data Pipeline Test Automation (Part 1)
Those who want to design universal data pipelines and ETL testing tools face a tough challenge because of the vastness and variety of technologies: Each data pipeline platform embodies a unique philosophy, architectural design, and set of operations. Some platforms are centered around batch processing, while others are centered around real-time streaming. While the nuances […]
Best Practices in Data Pipeline Test Automation
Data integration processes benefit from automated testing just like any other software. Yet finding a data pipeline project with a suitable set of automated tests is rare. Even when a project has many tests, they are often unstructured, do not communicate their purpose, and are hard to run. A characteristic of data pipeline development is the frequent […]
DataOps Highlights the Need for Automated ETL Testing (Part 2)
Click to learn more about author Wayne Yaddow. DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. ETL (i.e., extract, transform, load) projects are often devoid of automated testing. The […]
DataOps Highlights the Need for Automated ETL Testing (Part 1)
Click to learn more about author Wayne Yaddow. DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. ETL (i.e., extract, transform, load) projects are often devoid of automated testing. The […]
Becoming a Prized Data Warehouse and Data Integration Tester
Click to learn more about author Wayne Yaddow. Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. They have become a standard necessity for most modern organizations. Each business often uses one or more data […]
Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 3
Click to learn more about author Wayne Yaddow. In Part 1 and Part 2 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their […]
Avoid These Mistakes on Your Data Warehouse and BI Projects: Part 2
Click to learn more about author Wayne Yaddow. In Part 1 of this series, we described how data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations. Project sponsors seek to empower more and better data-driven decisions and actions throughout their enterprise; they intend to expand their user base for […]