Pull up a chair, pour yourself a fresh cup, and get ready to talk shop—because it’s time for Data Quality Coffee Series with Uncle Chip.
Data Quality When You Don’t Understand the Data: Data Quality Coffee With Uncle Chip #3
You can’t test for what you don’t understand. And so, we don’t. We skip it. We assume. Or worse, we wait until something breaks. What is the solution? Uncle Chip tells!
Webinar: A New, More Effective Approach To Data Quality Assessments
We introduce a new, more effective approach to data quality assessments, enabled by DataKitchen’s free open-source software
Why Data Quality Dimensions Fall Flat: Data Quality Coffee With Uncle Chip #2
In this playful yet pointed talk, Uncle Chip kicks things off by poking fun at the overcomplicated world of data quality dimensions that are rooted in an outdated era of static data, keeping teams locked in abstraction and inaction.
Why Data Quality Isn’t Worth The Effort: Data Quality Coffee With Uncle Chip #1
Data quality work is largely invisible. When everything is running smoothly, no one notices the effort behind it. But everyone notices the moment something breaks!
What Does Flossing One Tooth Have to Do with Data Quality?
Surprisingly, the answer may comes from an unusual place.
“Trusting Your Gut” 78.45% More Effective Than Data-Driven Decisions
Gartner/Harvard study: “Fire your data team tomorrow” and replace data and analytic teams with “affirmative decision AI agents”
Webinar: Announcing Actionable, Automated, & Agile Data Quality Scorecards – 2024
Announcing Actionable, Automated, & Agile Data Quality Scorecards
Unlocking Data Team Success: Are You Process-Centric or Data-Centric?
We want to share our observations about data teams, how they work and think, and their challenges. We’ve identified two distinct types of data teams: process-centric and data-centric. Understanding this framework offers valuable insights into team efficiency, operational excellence, and data quality.
How Data Quality Leaders Can Gain Influence And Avoid The Tragedy of the Commons
Using the ecological idea of the ‘Tragedy Of The Commons’ as a metaphor for the eternal issue of data quality, we talk about how data quality leaders can leverage Dale Carnegie’s 100-year-old ideas on influencing people and wrapping this improvement process with DataOps iterative improvement.
