Your organization’s data quality transformation is waiting for someone to take the first step. The open source tools are available, the methodologies are proven, and the need is obvious. . The revolution starts with you. What are you waiting for?
When Timing Goes Wrong: How Latency Issues Cascade Into Data Quality Nightmares
Timing is EVERYTHING. How Latency Issues Spawn Data Quality Problems
Webinar: A Guide to the Six Types of Data Quality Dashboards
In an exciting webinar, we discuss the six major types of Data Quality Dashboards
Data Quality Testing: A Shared Resource for Modern Data Teams
Data quality is not a problem any single role can solve in isolation. The complexity and scale of modern data ecosystems necessitate a collaborative approach, where quality testing serves as a shared infrastructure across all data and analytics roles.
How I Broke Our SLA and Delighted Our Customer
Failing the SLA was the price we paid for trust. And it was worth every second.
Is Your Team in Denial about Data Quality? Here’s How to Tell
Data quality problems are ignored, rationalized, or swept aside. How do you tell if your team is in denial about data quality? Uncle Chip has provided a bingo card … play with your data team!
The Data Quality Coffee Series With Uncle Chip
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Uncle Chip kicks things off by poking fun at the overcomplicated world of data quality dimensions that are rooted in an outdated era of static data, keeping teams locked in abstraction and inaction.