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Data Quality Based On Dama
Free Download Data Quality Based On Dama
Published 8/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 923.20 MB | Duration: 1h 57m
Master the key principles of Data Quality and learn how to profile, cleanse, monitor, and govern your data effectively
What you'll learn
Understand what data quality is and why it is essential for effective data management
Identify the key dimensions of data quality and how to measure them with practical metrics
Learn how to design and implement data quality rules, policies, and standards
Discover the main roles and responsibilities in a successful data quality program
Apply profiling, cleansing, and monitoring techniques to ensure reliable data
Integrate data quality into operational processes to increase efficiency and trust
Explore real use cases where data quality directly impacts business performance
Develop a sustainable and scalable approach to long-term data quality management
Requirements
Familiarity with data-related terminology can be helpful, but no prior knowledge is required
Description
Do you want to ensure that your organization's data is reliable, consistent, and fit for decision-making? Are you looking to detect and fix data issues before they impact operations or strategy? Then this course, "Data Quality in Data Governance Based on DAMA", is exactly what you need.In this course, you will explore the core principles of Data Quality and learn how to apply them within the DAMA-DMBOK framework. You'll understand how to profile, cleanse, monitor, and standardize data across your systems to ensure accuracy, completeness, consistency, and timeliness.We'll cover key topics such as defining quality dimensions, creating validation rules and standards, implementing continuous monitoring processes, and addressing real-world data quality challenges. You'll also learn how to embed Data Quality into broader governance initiatives and how to align people, processes, and tools for sustainable improvement.This course combines theory, practical guidance, and hands-on case studies to help you tackle the most common Data Quality issues across industries.Whether you're a data professional, a business analyst, or simply someone who works with data and wants to improve its reliability, this course offers a structured, flexible, and practical path to mastering Data Quality.Enroll now and learn how to turn poor data into powerful insights, driving efficiency, trust, and value across your organization!
Overview
Section 1: Introduction to Data Quality
Lecture 1 Definition of Data Quality
Lecture 2 Importance of Data Quality in Organizations
Lecture 3 Relationship Between Data Quality and Data Governance
Section 2: Business Drivers for Data Quality
Lecture 4 Factors Driving the Need to Manage Data Quality
Lecture 5 Impact of Data Quality on Operations and Decision-Making
Lecture 6 Examples of Common Problems Caused by Poor Data Quality
Section 3: Principles and Objectives of Data Quality Management
Lecture 7 Key Principles to Ensure Data Quality
Lecture 8 Accuracy: Data That Accurately Reflects Reality
Lecture 9 Integrity: Completeness of Required Data
Lecture 10 Consistency: Uniformity of Data Within Its Context
Lecture 11 Timeliness: Data Available When Needed
Lecture 12 Uniqueness: Elimination of Duplicates and Redundancies
Section 4: Key Activities in Data Quality Management
Lecture 13 Data Profiling and Quality Analysis
Lecture 14 Defining Business Rules and Quality Standards
Lecture 15 Continuous Monitoring and Measurement of Data Quality
Lecture 16 Data Cleansing and Error Correction
Lecture 17 Designing Operational Procedures for Data Quality
Section 5: Tools and Techniques for Data Quality
Lecture 18 Tools for Data Profiling and Analysis
Lecture 19 Solutions for Data Transformation and Validation
Lecture 20 Monitoring Techniques and Quality Reporting
Section 6: Governance in Data Quality Management
Lecture 21 Importance of Governance to Ensure Data Quality
Lecture 22 Roles and Responsibilities in Data Quality Management
Lecture 23 Policies and Standards for Data Quality
Section 7: Best Practices for Implementing a Data Quality Program
Lecture 24 Key Success Factors for Effective Data Quality Management
Lecture 25 Common Challenges and Lessons Learned From Data Quality Projects
Lecture 26 Strategies for Sustainable and Scalable Processes
Section 8: Practical Use Cases in Data Quality Management
Lecture 27 Case 1: Duplicate Resolution in a CRM System
Lecture 28 Case 2: Implementing Quality Monitoring in a Data Warehouse
Lecture 29 Case 3: Data Profiling and Cleansing in Legacy System Integration
Lecture 30 Case 4: Defining Business Rules to Ensure Master Data Consistency
Anyone who wants to understand how to ensure high-quality data to support reliable and efficient decision-making,Professionals who want to apply the DAMA-DMBOK framework to design and implement data quality initiatives,Individuals with no prior experience in data who want to learn the fundamentals of data quality and its business impact,Managers and team leaders seeking to improve data reliability and governance across their teams and departments,Students and recent graduates interested in building a solid foundation in one of the most in-demand areas of data management,Data analysts, developers, or IT professionals who want to strengthen their skills in profiling, cleansing, and monitoring data,Business consultants looking to incorporate data quality best practices into their projects and client solutions,Entrepreneurs or professionals from any sector aiming to improve their operations through better data practices
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