Hey Anshal \
Thats a great question and thanks for posting on QnandA platform,
So, the data quality, right? First off, you gotta get comfortable with your data. data profiling and discovery. Get to know the ins and outs of your data sources.
Next up,is data cleaning! Just like tidying up your room, data cleansing and transformation help standardize things, squash errors, and tidy up duplicates.
for validation and monitoring? Set up some rules to make sure your data stays clean and keep an eye on things with real-time monitoring.
And don't forget about metadata – it's like your data's ID card. Keep track of where it's been, what it's up to, and who's been tinkering with it. and importantly solid error handling and logging, you'should be ready to tackle them like a pro.
You have got this and all the very best
If this answer helps kindly accept the answer thanks much.