Blog
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.
Announcing Open Source DataOps Data Quality TestGen 3.0
Now With Actionable, Automatic, Data Quality Dashboards. Learn about DataOps Data Quality TestGen 3.0.
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...
The Five Use Cases in Data Observability: Mastering Data Production
 The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs. This blog...
The Five Use Cases in Data Observability: Effective Data Anomaly Monitoring
The Five Use Cases in Data Observability: Effective Data Anomaly Monitoring (#2) Ensuring the accuracy and timeliness of data ingestion is a cornerstone for maintaining the integrity of data systems. Data ingestion monitoring, a critical aspect of Data...
The Five Use Cases in Data Observability: Data Quality in New Data Sources
The Five Use Cases in Data Observability: Data Quality in New Data Sources (#1) Ensuring their quality and integrity before incorporating new data sources into production is paramount. Data evaluation serves as a safeguard, ensuring that only cleansed and...
The Five Use Cases in Data Observability: Overview
Harnessing Data Observability Across Five Key Use Cases The ability to monitor, validate, and ensure data accuracy across its lifecycle is not just a luxury—it’s a necessity. Data observability extends beyond simple anomaly checking, offering deep insights into...
DataOps and Data Observability Education And Certification Offerings From DataKitchen
DataKitchen Training And Certification Offerings For Individual contributors with a background in Data Analytics/Science/Engineering     Overall Ideas and Principles of DataOps DataOps Cookbook (200 page book over 30,000 readers, free): DataOps Certification (3...
