Data Quality Management: Rules, Good Data & Bad Data скачать в хорошем качестве

Data Quality Management: Rules, Good Data & Bad Data

The platform enables users to define and enforce data quality rules, such as checks for duplicity, completeness, and consistency. These rules can be applied across different data sources, ensuring continuous monitoring and improvement of data quality across pipelines, thereby reducing manual effort and increasing data trustworthiness. Data Quality Monitor (DQM) empowers you to define, enforce, and automate data quality rules for all your pipelines. Whether you’re running batch jobs or incremental updates, DQM’s zero-code/low-code templates let you easily customize and deploy rules like duplicity checks, completeness, and consistency—across any data source. See how DQM classifies good vs bad data, highlights quality issues, and helps teams continuously monitor and improve data trustworthiness with actionable insights. 📅 Timestamps: 0:00 - Introduction 0:26 - Three Pillars of Data Quality 0:33 - Zero/Low Code Rule Systems 0:49 - Duplicity Check Example 1:20 - Transactional Type and Domain Checks 1:48 - Duplicity, Domain, and Attribute Checks 2:24 - Custom Operators for Versatility 2:42 - Industry Use Case (Pharmaceutical Insurance) 3:38 - Reusing, Importing, and Exporting Rules 3:54 - SQL Queries and Expressions 4:25 - Metrics Comparison for Financial Data 4:45 - Segregating Good and Bad Records 5:13 - Auto-Healing and Transformations 5:58 - Contact Information and Free Demo 📧 Contact Us: contact@datagaps.com 🌐 Free Demo: Scan the QR code in the video! DataOps Data Quality Monitor - Monitor data quality in your Data Pipelines, AI & Analytics using Gen AI DataOps DQ Monitor - https://www.datagaps.com/dataops-data... Start a Free Trial - https://www.datagaps.com/data-quality... 🎬 Video Highlights: Snippet 1: Introduction to the Platform: Data Quality Monitor -    • Introduction to the Platform: Data Quality...   Snippet 2: Data Quality Management: Rules, Good Data & Bad Data -    • Data Quality Management: Rules, Good Data ...   Snippet 3: Tracking Data Quality Score Through Models and Lineage -    • Tracking Data Quality Score Through Models...   Snippet 4: Profiling + Observability: How DQM Catches Data Anomalies -    • Profiling + Observability: How DQM Catches...   Snippet 5: Generative AI Meets Data Quality: Rule Creation Simplified -    • Generative AI Meets Data Quality: Rule Cre...   #DataQuality #DataRules #GoodData #BadData #DataTrust #DataManagement #DQMDemo