Blog
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.
Webinar: DataOps For Beginners – 2024
“That should take two hours, not two months. Can’t your Data & Analytics Team go any faster?”“The executives’ dashboard broke! The data’s wrong! Can I ever trust our data?”If you’ve ever heard (or had) these complaints about speed-to-insight or data...
Read White Paper: Data Quality The DataOps Way
Read Our New White Paper: Data Quality The DataOps Way Data quality isn’t just a technical hurdle—it’s a strategic necessity in the data-driven world. Traditional methods fall short, but the DataOps approach to data quality offers a transformative path forward. It...
Data Quality Power Moves: Scorecards & Data Checks for Organizational Impact
A DataOps Approach to Data Quality The Growing Complexity of Data Quality Data quality issues are widespread, affecting organizations across industries, from manufacturing to healthcare and financial services. According to DataKitchen’s 2024 market research, conducted...
From Cattle to Clarity: Visualizing Thousands of Data Pipelines with Violin Charts
From Cattle to Clarity: Visualizing Thousands of Data Pipelines with Violin Charts Most data teams work with a dozen or a hundred pipelines in production. What do you do when you have thousands of data pipelines in production? How do you understand what is...
Data Quality Circles: The Key to Elevating Data and Analytics Team Performance
Data Quality Circles: The Key to Elevating Data and Analytics Team Performance Introduction: The Pursuit of Quality in Data and Analytic Teams. According to a study by HFS Research, 75 percent of business executives do not have a high level of trust in their data. ...
2024 Gartner Market Guide To DataOps
2024 Gartner Market Guide To DataOps We at DataKitchen are thrilled to see the publication of the Gartner Market Guide to DataOps, a milestone in the evolution of this critical software category. As the pioneer in the DataOps category, we are proud to have laid the...
DataKitchen’s Data Quality TestGen Found 18 Potential Data Quality Issues In A Few Minutes!
DataKitchen’s Data Quality Testgen Found 18 Potential Data Quality Issues In A Few Minutes (Including Install Time) On Data.Boston.Gov Building Permit Data! Imagine a free tool that you can point at any dataset and find actionable data quality issues immediately! It...
Navigating the Storm: How Data Engineering Teams Can Overcome a Data Quality Crisis
Navigating the Storm: How Data Engineering Teams Can Overcome a Data Quality Crisis Ah, the data quality crisis. It's that moment when your carefully crafted data pipelines start spewing out numbers that make as much sense as a cat trying to bark. You know you're in...
How Three Small Pharma Companies Used DataKitchen to Achieve Commercial Launch Success and Skyrocket to $100 Billion in Acquisition Value
Why Did Three Pharmaceutical Companies Preparing for Their Commercial Launch (That Eventually Sold for $100 Billion) Choose DataKitchen? Three pharma companies recently made headlines by securing successful exits totaling $100 billion. What’s their common denominator?...
Data Observability and Data Quality Testing Certification Series
Data Observability and Data Quality Testing Certification Series We are excited to invite you to a free four-part webinar series that will elevate your understanding and skills in Data Observation and Data Quality Testing. This series is crafted for professionals...
The Five Use Cases in Data Observability: Ensuring Accuracy in Data Migration
The Five Use Cases in Data Observability: Accuracy in Data Migration (#5) Data migration projects, such as moving from on-premises infrastructure to the cloud, are critical and complex projects that involve transferring data across different systems while...
The Five Use Cases in Data Observability: Fast, Safe Development and Deployment
The Five Use Cases in Data Observability: Fast, Safe Development & Deployment (#4) The integrity and functionality of new code, tools, and configurations during the development and deployment stages are crucial. This blog post delves into the third critical...
