Immediately Detect Knowledge High quality Points and Determine their Causes
In at this time’s data-driven world, organizations rely closely on correct information to make crucial enterprise selections. As a accountable and reliable Knowledge Engineer, making certain information high quality is paramount. Even a short interval of displaying incorrect information on a dashboard can result in the speedy unfold of misinformation all through your entire group, very like a extremely infectious virus spreads by way of a residing organism.
However how can we forestall this? Ideally, we might keep away from information high quality points altogether. Nevertheless, the unhappy fact is that it’s inconceivable to fully forestall them. Nonetheless, there are two key actions we are able to take to mitigate the influence.
- Be the primary to know when an information high quality situation arises
- Decrease the time required to repair the problem
On this weblog, I’ll present you learn how 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 shortly determine the reason for any failures. In the event you’re searching for an alternate testing framework, try my article on An Introduction into Nice Expectations with python.
