Learn how to Immediately Detect Information High quality Points and Determine their Causes
In right now’s data-driven world, organizations rely closely on correct information to make crucial enterprise choices. As a accountable and reliable Information Engineer, making certain information high quality is paramount. Even a short interval of displaying incorrect information on a dashboard can result in the fast unfold of misinformation all through your entire group, very similar to a extremely infectious virus spreads by means of a residing organism.
However how can we forestall this? Ideally, we’d keep away from information high quality points altogether. Nonetheless, the unhappy fact is that it’s unattainable to utterly forestall them. Nonetheless, there are two key actions we are able to take to mitigate the impression.
- Be the primary to know when an information high quality problem arises
- Reduce the time required to repair the problem
On this weblog, I’ll present you the right way to implement the second level immediately in your code. I’ll create an information pipeline in Python utilizing generated information from Mockaroo and leverage Tableau to rapidly establish the reason for any failures. Should you’re in search of another testing framework, take a look at my article on An Introduction into Nice Expectations with python.
