Summary of the Melody Chien from Gartner Presentation: “How Can You Leverage Technologies to Solve Data Quality Challenges?”
Webinar: Data Quality in a Medallion Architecture – 2024
Would you like help maintaining high-quality data across every layer of your Medallion Architecture?
A Guide to the Six Types of Data Quality Dashboards
Not all data quality dashboards are created equal. Their design and focus vary significantly depending on an organization’s unique goals, challenges, and data landscape. This blog delves into the six distinct types of data quality dashboards, examining how each fulfills a specific role in improving Data Quality.
The Race For Data Quality in a Medallion Architecture
The Medallion Data Lakehouse Architecture Has A Unique Set Of Data Quality Challenges. Find Out How To Take The Gold In This Tough Data Quality Race!
Webinar: DataOps For Beginners – 2024
If you’ve ever heard (or had) these complaints about speed-to-insight or data reliability, you should watch our webinar, DataOps for Beginners, on demand.
Read White Paper: Data Quality The DataOps Way
Traditional methods fall short, but the DataOps approach to data quality offers a transformative path forward.
Data Quality Power Moves: Scorecards & Data Checks for Organizational Impact
Webinar: Unlocking the Power of Data Observability and Quality Testing
From Cattle to Clarity: Visualizing Thousands of Data Pipelines with Violin Charts
What do you do when you have thousands of data pipelines in production? Is there a way that you can visualize what is happening in production quickly and easily?
DataKitchen’s Data Quality TestGen Found 18 Potential Data Quality Issues In A Few Minutes!
Imagine a free tool that you can point at any dataset and find actionable data quality issues immediately! I took DataKitchen’s Data Quality TestGen for a test drive on ~600k rows of Boston City data and found 18 data quality hygiene issues in a few minutes.
Navigating the Storm: How Data Engineering Teams Can Overcome a Data Quality Crisis
A data quality crisis in data engineering is more than a mere technical hiccup; it often signals deeper systemic issues within the team and organizational processes. Let’s delve into the root causes, symptoms, and strategies for rapid intervention and long-term improvement.
