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Announcing Open Source DataOps Data Quality TestGen 3.0

DataKitchen

Announcing DataOps Data Quality TestGen 3.0: Open-Source, Generative Data Quality Software. It assesses your data, deploys production testing, monitors progress, and helps you build a constituency within your company for lasting change. New Quality Dashboard & Score Explorer.

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Data Quality Power Moves: Scorecards & Data Checks for Organizational Impact

DataKitchen

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. 73% of data practitioners do not trust their data (IDC).

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Visualize data quality scores and metrics generated by AWS Glue Data Quality

AWS Big Data

AWS Glue Data Quality allows you to measure and monitor the quality of data in your data repositories. It’s important for business users to be able to see quality scores and metrics to make confident business decisions and debug data quality issues. An AWS Glue crawler crawls the results.

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No Python, No SQL Templates, No YAML: Why Your Open Source Data Quality Tool Should Generate 80% Of Your Data Quality Tests Automatically

DataKitchen

No Python, No SQL Templates, No YAML: Why Your Open Source Data Quality Tool Should Generate 80% Of Your Data Quality Tests Automatically As a data engineer, ensuring data quality is both essential and overwhelming. Everyone wants to write more tests, yet they somehow never get it done.

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Webinar: A New, More Effective Approach To Data Quality Assessments

DataKitchen

A New, More Effective Approach To Data Quality Assessments In DataKitchens recent webinar, CEO Christopher Bergh offered a compelling new approach to a timeless problem: how do we improve data quality in organizations where no one truly owns it, everyone needs it, and no one has the authority to enforce change?

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How Data Quality Leaders Can Gain Influence And Avoid The Tragedy of the Commons

DataKitchen

How Data Quality Leaders Can Gain Influence And Avoid The Tragedy of the Commons Data quality has long been essential for organizations striving for data-driven decision-making. Many organizations struggle with incomplete, inconsistent, or outdated data, making it difficult to derive reliable insights.

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Webinar: Data Quality in a Medallion Architecture – 2024

DataKitchen

Like an Olympic athlete training for the gold, your data needs a continuous, iterative process to maintain peak performance. We covered how Data Quality Testing, Observability, and Scorecards turn data quality into a dynamic process, helping you build accuracy, consistency, and trust at each layerBronze, Silver, and Gold.