Big Data Product QA

BRIEF

A tech startup in the US has developed a low code / no code framework for Big Data ELT that handles all data complexities in the backend. This frees customers from the hassle of data processing and allows them to get maximum benefit from the data.

Gamut QA helped achieve 95% product demo success resulting in reduced time to market with this product.

Extensive QA ensured high quality releases of this delightful / intuitive, fast and accurately functioning product.

CHALLENGES

Fast paced Product development with frequent changes
QA team had to be productive quickly by understanding product and domain
UI is the key differentiator of in this product and thus had to be tested extensively

SOLUTION

Special emphasis was placed on UI/UX which is a very important part of this product. Apart from reporting bugs, QA team’s approach was to improve the overall User Experience and intuitiveness
QA team automated part of the regression workflow to make the QA cycle faster to match the development pace
Advanced functionalities in the product like version control, error handling, automation and scheduling for jobs were tested rigorously, ensuring a robust release

BENEFITS

30% of total bugs raised were user workflow/UX related, that helped product meet enterprise standards and achieve intuitive user experience which is the product’s USP

15% of total bugs raised were enhancements that added value to the product acceptance and success
Maximum QA coverage accomplished with few thousand test cases written for existing functionality and more being added as QA scope increases
Time and cost of regression brought down by automation of redundant tasks