How one can Immediately Detect Information High quality Points and Determine their Causes
In immediately’s data-driven world, organizations rely closely on correct knowledge to make important enterprise choices. As a accountable and reliable Information Engineer, guaranteeing knowledge high quality is paramount. Even a short interval of displaying incorrect knowledge on a dashboard can result in the speedy unfold of misinformation all through the whole group, very like a extremely infectious virus spreads via a dwelling organism.
However how can we stop this? Ideally, we might keep away from knowledge high quality points altogether. Nevertheless, the unhappy fact is that it’s not possible to utterly stop them. Nonetheless, there are two key actions we are able to take to mitigate the affect.
- Be the primary to know when a knowledge high quality subject arises
- Reduce the time required to repair the problem
On this weblog, I’ll present you the right way to implement the second level straight in your code. I’ll create a knowledge pipeline in Python utilizing generated knowledge from Mockaroo and leverage Tableau to rapidly determine the reason for any failures. When you’re on the lookout for another testing framework, take a look at my article on An Introduction into Nice Expectations with python.