DataKitchen

FEBRUARY 20, 2025

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.

Data Quality 183

Data Quality Scorecard Testing Dashboards 183

DataKitchen

SEPTEMBER 18, 2024

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).

Scorecard 177

Scorecard Data Quality Measurement Testing 177

AWS Big Data

JUNE 6, 2023

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.

Data Quality 78

Data Quality Metrics Visualization Dashboards 78

DataKitchen

FEBRUARY 17, 2025

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.

Data Quality 183

Data Quality Testing Scorecard Data-driven 183

DataKitchen

MARCH 13, 2025

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 Many organizations struggle with incomplete, inconsistent, or outdated data, making it difficult to derive reliable insights.

Data Quality 189

Data Quality Scorecard Data-driven Cost-Benefit 189

DataKitchen

DECEMBER 6, 2024

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.

Data Quality 130

Data Quality Scorecard Testing Strategy 130

Jet Global

SEPTEMBER 1, 2023

These include data privacy and security concerns, model accuracy and bias challenges, user perception and trust issues, and the dependency on data quality and availability. Data Privacy and Security Concerns: Embedded predictive analytics often require access to sensitive user data for accurate predictions.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52