Environment friendly Testing of ETL Pipelines with Python | by Robin von Malottki | Oct, 2024
Easy methods to Immediately Detect Information High quality Points and Establish their Causes
In immediately’s data-driven world, organizations rely closely on correct information to make crucial enterprise choices. As a accountable and reliable Information Engineer, guaranteeing information high quality is paramount. Even a quick interval of displaying incorrect information on a dashboard can result in the fast unfold of misinformation all through the whole group, very similar to a extremely infectious virus spreads by way of a dwelling organism.
However how can we forestall this? Ideally, we might keep away from information high quality points altogether. Nonetheless, the unhappy fact is that it’s inconceivable to fully forestall them. Nonetheless, there are two key actions we will take to mitigate the affect.
- Be the primary to know when an information high quality concern arises
- Reduce the time required to repair the problem
On this weblog, I’ll present you how one can implement the second level instantly 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. For those who’re in search of another testing framework, try my article on An Introduction into Great Expectations with python.
