priteshgeek

1. 📘 Introduction & Overview 🔍 What is Row-Level Validation? Row-Level Validation is a data validation technique that ensures the integrity, consistency, and correctness of individual data rows within a dataset—often at ingestion, storage, or pre-processing stages. In a DevSecOps context, it is the process of automatically validating each data record that flows through pipelines, … Read more

1. Introduction & Overview 🔍 What Are Data Contracts? Data Contracts are formal, versioned agreements between data producers and consumers, defining the structure, semantics, and quality expectations of the data being exchanged. Much like an API contract in software, a data contract ensures reliable and predictable data pipelines, minimizing unexpected schema changes and broken workflows. … Read more

1. Introduction & Overview What is Drift Detection? Drift Detection is the process of identifying and managing configuration changes that occur outside of an organization’s defined Infrastructure as Code (IaC) or policy templates. It plays a critical role in ensuring system integrity, compliance, and security in DevSecOps pipelines by detecting “drifts” from the intended state. … Read more

✅ Introduction & Overview What is Test Data Management (TDM)? Test Data Management (TDM) is the practice of creating, managing, and provisioning test data for application development, testing, and deployment. In DevSecOps, TDM ensures secure, compliant, and efficient test data usage throughout the CI/CD pipeline. History & Background Why is TDM Relevant in DevSecOps? 🧩 … Read more

📌 1. Introduction & Overview 🔍 What is Schema Validation? Schema Validation is the process of ensuring that data adheres to a predefined structure or format—known as a schema. This validation helps to ensure data consistency, prevent malformed data from propagating through systems, and safeguard against potential security vulnerabilities due to untrusted inputs. In the … Read more

1. Introduction & Overview What is Data Anomaly Detection? Data Anomaly Detection refers to the process of identifying data points, events, or observations that deviate significantly from the expected pattern in datasets. These anomalies often signal critical issues such as: In DevSecOps, anomaly detection is used for proactive monitoring and mitigation across development, security, and … Read more

📌 Introduction & Overview What is Great Expectations? Great Expectations (GE) is an open-source Python-based data validation, documentation, and profiling framework. It helps teams define, test, and document expectations about data as it flows through pipelines, ensuring that data quality issues are detected early and automatically History or Background Why is it Relevant in DevSecOps? … Read more

1. Introduction & Overview What is Data Quality Testing? Data Quality Testing is the process of systematically validating, verifying, and monitoring data to ensure it is accurate, complete, consistent, timely, and reliable throughout its lifecycle. In modern systems, especially those relying on data pipelines, data lakes, or ML models, the quality of data directly influences … Read more

1. Introduction & Overview What is Integration Testing? Integration Testing is a level of software testing where individual units or components are combined and tested as a group to expose faults in the interactions between them. It validates that multiple components work together correctly after being integrated. History and Background Why Is It Relevant in … Read more

1. Introduction & Overview 🔍 What is Unit Testing? Unit Testing is a software testing method where individual units or components of a program are tested in isolation from the rest of the system. A unit is typically the smallest testable part of an application, such as a function or method. The goal of unit … Read more