Skip to main content
Master Data Management And Data Governance Complete Self-Assessment Guide

Master Data Management And Data Governance Complete Self-Assessment Guide

$199.00
When you get access:
Course access is prepared after purchase and delivered via email
How you learn:
Self-paced • Lifetime updates
Your guarantee:
30-day money-back guarantee — no questions asked
Who trusts this:
Trusted by professionals in 160+ countries
Toolkit Included:
Includes a practical, ready-to-use toolkit with implementation templates, worksheets, checklists, and decision-support materials so you can apply what you learn immediately - no additional setup required.
Adding to cart… The item has been added

Master Data Management And Data Governance Complete Self-Assessment Guide



Course Overview

This comprehensive course provides a thorough understanding of Master Data Management (MDM) and Data Governance, enabling participants to effectively manage and govern their organization's data. Upon completion, participants will receive a certificate issued by The Art of Service.



Course Features

  • Interactive and engaging content
  • Comprehensive and personalized learning experience
  • Up-to-date and practical knowledge
  • Real-world applications and case studies
  • High-quality content developed by expert instructors
  • Certificate issued upon completion
  • Flexible learning options
  • User-friendly and mobile-accessible platform
  • Community-driven discussion forums
  • Actionable insights and hands-on projects
  • Bite-sized lessons for easy learning
  • Lifetime access to course materials
  • Gamification and progress tracking features


Course Outline

Module 1: Introduction to Master Data Management (MDM)

  • Definition and importance of MDM
  • Key components of MDM
  • Benefits of implementing MDM
  • Challenges and risks associated with MDM

Module 2: Data Governance Fundamentals

  • Definition and importance of Data Governance
  • Key components of Data Governance
  • Benefits of implementing Data Governance
  • Challenges and risks associated with Data Governance

Module 3: Data Quality and Integrity

  • Importance of data quality and integrity
  • Types of data quality issues
  • Data quality metrics and benchmarks
  • Best practices for ensuring data quality and integrity

Module 4: Data Security and Compliance

  • Importance of data security and compliance
  • Types of data security threats
  • Data security metrics and benchmarks
  • Best practices for ensuring data security and compliance

Module 5: Data Architecture and Modeling

  • Importance of data architecture and modeling
  • Types of data architecture
  • Data modeling techniques and tools
  • Best practices for designing and implementing data architecture

Module 6: Data Integration and Interoperability

  • Importance of data integration and interoperability
  • Types of data integration techniques
  • Data interoperability standards and protocols
  • Best practices for ensuring data integration and interoperability

Module 7: Data Warehousing and Business Intelligence

  • Importance of data warehousing and business intelligence
  • Types of data warehousing architectures
  • Business intelligence tools and techniques
  • Best practices for designing and implementing data warehousing and business intelligence solutions

Module 8: Big Data and Analytics

  • Importance of big data and analytics
  • Types of big data analytics techniques
  • Big data tools and technologies
  • Best practices for implementing big data and analytics solutions

Module 9: Cloud Computing and Data Management

  • Importance of cloud computing and data management
  • Types of cloud computing models
  • Cloud data management best practices
  • Challenges and risks associated with cloud data management

Module 10: Data Governance and Compliance in the Cloud

  • Importance of data governance and compliance in the cloud
  • Cloud data governance best practices
  • Cloud compliance frameworks and standards
  • Challenges and risks associated with cloud data governance and compliance

Module 11: Data Management and Analytics in the Internet of Things (IoT)

  • Importance of data management and analytics in IoT
  • IoT data management best practices
  • IoT analytics techniques and tools
  • Challenges and risks associated with IoT data management and analytics

Module 12: Artificial Intelligence (AI) and Machine Learning (ML) in Data Management

  • Importance of AI and ML in data management
  • AI and ML techniques and tools
  • Best practices for implementing AI and ML in data management
  • Challenges and risks associated with AI and ML in data management

Module 13: Data Management and Analytics in Blockchain

  • Importance of data management and analytics in blockchain
  • Blockchain data management best practices
  • Blockchain analytics techniques and tools
  • Challenges and risks associated with blockchain data management and analytics

Module 14: Data Management and Analytics in Cybersecurity

  • Importance of data management and analytics in cybersecurity
  • Cybersecurity data management best practices
  • Cybersecurity analytics techniques and tools
  • Challenges and risks associated with cybersecurity data management and analytics

Module 15: Data Management and Analytics in Healthcare

  • Importance of data management and analytics in healthcare
  • Healthcare data management best practices
  • Healthcare analytics techniques and tools
  • Challenges and risks associated with healthcare data management and analytics

Module 16: Data Management and Analytics in Finance

  • Importance of data management and analytics in finance
  • Finance data management best practices
  • Finance analytics techniques and tools
  • Challenges and risks associated with finance data management and analytics

Module 17: Data Management and Analytics in Retail

  • Importance of data management and analytics in retail
  • Retail data management best practices
  • Retail analytics techniques and tools
  • Challenges and risks associated with retail data management and analytics

Module 18: Data Management and Analytics in Manufacturing

  • Importance of data management and analytics in manufacturing
  • Manufacturing data management best practices
  • Manufacturing analytics techniques and tools
  • Challenges and risks associated with manufacturing data management and analytics

Module 19: Data Management and Analytics in Government

  • Importance of data management and analytics in government
  • Government data management best practices
  • Government analytics techniques and tools
  • Challenges and risks associated with government data management and analytics

Module 20: Data Management and Analytics in Education

  • Importance of data management and analytics in education
  • Education data management best practices
  • Education analytics techniques and tools
  • Challenges and risks associated with education data management and analytics


Certificate of Completion

Upon completing all 20 modules, participants will receive a Certificate of Completion issued by The Art of Service.



Target Audience

This course is designed for professionals who want to gain a comprehensive understanding of Master Data Management and Data Governance, including:

  • Data management professionals
  • Data governance professionals
  • IT professionals
  • Business analysts
  • Business intelligence professionals
  • Data scientists
  • Analytics professionals


Prerequisites

There are no prerequisites for this course. However, a basic understanding of data management and data governance concepts is recommended.



Duration

This course is self-paced and can be completed in 40 hours.

!