What Are The Challenges Of A Data Factory
DataOps Platform for Integrated Data Testing & Production Monitoring
DataOps is a set of practices and tools used by Big Data teams to increase velocity, reliability, and quality of data analytics. It emphasizes communication, collaboration, integration, automation, measurement and cooperation between data scientists, analysts, data/ETL (extract, transform, load) engineers, information technology (IT), and quality assurance/governance. It aims to help organizations rapidly produce insight, turn that insight into operational tools, and continuously improve analytic operations and performance.
DataOps Pipeline

TDD | Agile | Unit Test | Regression Test | Release Sign-off | User Acceptance | Monitoring | Compliance | Dashboard | Alerts & Notification
Data Auditing – The Missing Component of the Data Strategy
iCEDQ is specialized in-memory rules engine designed to Validate and reconcile data. Users create and store these rules permanently in the repository.

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