Saturday, April 20, 2024

Do not Repair Unhealthy Knowledge High quality, Do This As an alternative

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Individuals don’t know what they imply after they discuss information high quality.

Towards Data Science
Picture by No Revisions on Unsplash

A number of years in the past, our information platform workforce aimed to pinpoint the first considerations of our information customers. We performed a survey amongst people interacting with our information platform, and unsurprisingly, the principle concern highlighted was information high quality.

The preliminary response, attribute of our engineering mindset, was to develop information high quality tooling. We launched an inner device named Contessa. Regardless of being considerably cumbersome and necessitating vital guide configuration, Contessa facilitated checks for traditional dimensions of knowledge high quality, encompassing consistency, timeliness, validity, uniqueness, accuracy and completeness. After operating the device for a few months with tons of of knowledge high quality checks we concluded that:

  • Knowledge high quality checks sometimes assisted information customers in discovering, in a shorter timeframe, that the information was compromised and couldn’t be relied upon.
  • Regardless of the frequent execution of knowledge high quality checks, there was no noticeable enchancment within the subjective notion of knowledge high quality.
  • For a good portion of points, significantly these recognized by means of automated information high quality checks comparable to consistency or validity, no corrective actions have been ever taken.

Survey and goal measurement are helpful instruments, however nothing can exchange a dialogue over espresso and cake, as Jane Carruthers writes in her e book, “The Chief Knowledge Officer’s Playbook”. Certainly, I like to recommend this to anyone, as one-on-one conversations helped us uncover one other essential angle of the state of affairs. A few of these conversations unfolded as follows:

“Hey, you say, that information high quality is poor, what do you imply by that?”

#1 Pricing enterprise analyst: “We’re engaged on establishing worth for the ancillary product X. Within the dataset we use, we’re lacking information on what was the precise income from the product X per every order. We now have this dataset , but it surely incorporates solely anticipated worth of the income from X at time of the acquisition. We are able to see additionally the precise income per product, however not on the order granularity.”



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