The right way to Immediately Detect Information High quality Points and Establish their Causes
In in the present day’s data-driven world, organizations rely closely on correct knowledge to make crucial enterprise selections. 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 fast unfold of misinformation all through the complete group, very similar to a extremely infectious virus spreads by a residing organism.
However how can we forestall this? Ideally, we’d keep away from knowledge high quality points altogether. Nevertheless, the unhappy fact is that it’s unattainable to fully forestall them. Nonetheless, there are two key actions we will take to mitigate the influence.
- Be the primary to know when a knowledge high quality concern arises
- Reduce the time required to repair the difficulty
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. In the event you’re in search of another testing framework, try my article on An Introduction into Great Expectations with python.
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