Introduction & Overview DataOps is a methodology that applies agile practices, DevOps principles, and automation to data management, aiming to deliver high-quality data pipelines efficiently. GitOps, a DevOps practice that…
Introduction & Overview In the rapidly evolving landscape of data management, DataOps has emerged as a pivotal methodology that applies agile, DevOps, and lean manufacturing principles to streamline data analytics…
Introduction & Overview What is Row-Level Validation? Row-Level Validation is a critical process in DataOps that ensures each individual record (or row) in a dataset adheres to predefined quality rules,…
Introduction & Overview Data contracts have emerged as a pivotal concept in modern data engineering, particularly within the DataOps framework. They address the critical need for reliable, consistent, and trusted…
Introduction & Overview In the dynamic world of data management, ensuring the reliability and accuracy of data pipelines and machine learning (ML) models is paramount. Drift detection is a critical…
Introduction & Overview Test Data Management (TDM) is a critical discipline in DataOps, enabling organizations to deliver high-quality data for testing while maintaining security, compliance, and efficiency. This tutorial explores…
Introduction & Overview Schema validation ensures that data adheres to a predefined structure, format, and set of rules before it is processed, stored, or analyzed in a DataOps pipeline. It…
Introduction & Overview What is Data Anomaly Detection? Data anomaly detection is the process of identifying patterns or data points that deviate significantly from expected behavior in datasets. These anomalies,…
Introduction & Overview What is Great Expectations? Great Expectations (GX) is an open-source Python-based framework designed for data validation, documentation, and profiling. It enables data teams to define “Expectations”—assertions about…
Introduction & Overview Data Quality Testing (DQT) ensures that data used in analytics, machine learning, and business intelligence is accurate, consistent, and reliable. In DataOps, a methodology that applies DevOps…