What are the similarities and differences in Software Testing and Data Science?

The world is moving towards AI systems in the fastest way anyone can imagine – and at Moolya we are observing closely this radical shift. We have initiated a number of ways in which we would be ready for this shift and one of the ways to do so is with Learning with Moolya initiative.
I have been fortunate enough to work in both the fields, i.e, Software Testing, and Data Science – and we are observing interesting patterns in both. The graphic below might reveal some details for you :
This is one of the most important skills – both in Data Science and Software testing. A Software tester while testing always asks questions in order to discover information that could affect the quality of the product.
Whereas a data scientist – asks questions to the system, identify problems – then ask questions of the data collected. A data scientist aims to reveal information by asking questions to data.
Never 100% accurate 
In data science – you will never have 100% data in an ideal state. You will always have a subset of data with you – to make decisions on. The more accurate and clean your collected data is – the better your decisions are.
Finding 100% bugs in software is never possible – a good tester will reveal enough bugs that satisfy quality criteria given, based on context.
Improves with More information 
Data science-based algorithms, systems, and AI – improves with more data. It learns with the more data gathered – which helps systems to identify patterns in the problem they are solving.
If better information is given to a testing team – it will perform better.
Better Methods leads to a better outcome
“Data Science” is a branch of science and so is Software Testing. There are scientific methods that are defined, being improved each day. A Software testing area has been improved greatly in the last 2 decades where better methodologies to test, good tools and technologies invented.
Data science has been greatly improved with an introduction to open source systems with good visualization tools, data mining tools, and research done is building fast and accurate algorithms. Do you know about XgBoost? This is an algorithm that top data scientists use for the most accurate prediction and fastest results.
Data Science session recall:
Riyaj Sheikh |Chief Data Officer |Moolya Testing

You May Also Like