Validata Blog: Talk AI-powered Testing

During 2021, many banks got into the headlines because of software malfunctions that caused serious inconveniences to their customers. A phenomenally simple software error can affect the life of millions of people in the most direct and negative way. It is estimated that software failures cost the enterprise software market approximately $61B annually, and over 620 million developer hours a year, are wasted on debugging software failures.

The increased volume and variety of data that companies are managing nowadays makes it more challenging to ensure that data is of good quality. Now data in companies come from diverse data sources, with different characteristics and levels of complexity.

Synthetic data is data that is manually or artificially created contains all the characteristics of production minus the sensitive content, and is used for a wide range of use cases, including as test data for new products and tools, for model validation, and in AI model training. 

An ETL Pipeline is a set of processes that include the extraction of data from a source, its transformation, and then loading into the target data warehouse, data mart or database for data analysis or any other purpose. The main purpose is to centralize data across the company and present the ‘single version of the truth’.