Repost Linkedin : https://www.linkedin.com/posts/yacine-bekka_dataquality-data-learning-activity-7039189646546718721-UK-H?utm_source=share&utm_medium=member_desktop
Do you ever feel like you’re struggling to explain the data jargon to your coworkers? 🤯
Trust me, I know what you feel!
So let me share with you, the definition I use to explain data quality to a non-data audience:
First, you can think of data as a digital twin of a real thing.
As an example, customer data in your CRM are the digital twins of your “real” customers.
Data quality is about how accurate that digital twin is compared to the real thing….
But here’s the thing: quality is a subjective concept.
Let’s take a pair of shoes… What makes them high-quality?
It depends on who’s wearing them and what they’re wearing them for, right?
Well, it’s the same with data! Quality will depend a lot on the usage.
To keep with the shoe analogy, managing data quality is a lot like managing quality in a shoe factory. It requires to :
- Define quality requirements
- Regularly check that the data meets your expectations
- Address any complaints from consumers
- Investigate the causes of quality issues.
It’s not always fun, but it’s definitely necessary !
Are your data as good as stilettos on the rugby field or do you have your data cleats on? 😂