Professional Data Management and Business Intelligence

About the Course:

The "Professional Data Management and Business Intelligence" course is designed to provide participants with in-depth knowledge and skills in managing data and leveraging business intelligence tools. The course will cover essential topics, from data governance and quality to the latest technologies and risk management strategies, tailored specifically for archiving document sections and documentation warehouses.

Objectives:

By the end of this course, participants will be able to:

• Understand the fundamentals of data management and business intelligence.
• Develop strategic plans for data management and business intelligence specific to facility operations.
• Implement new and suggested technologies for data management and business intelligence.
• Utilize technology and automation to enhance data management and business intelligence processes.
• Identify and mitigate risks associated with data management and business intelligence.
• Ensure quality standards in data management and business intelligence.

Who Should Attend the Course:

• Data Managers
• Business Intelligence Analysts
• IT Managers / Data Architects
• Professionals involved in data management and business intelligence

Professional Experience and Courses Delivered:

• Data Management Strategies
• Business Intelligence Tools and Techniques
• Advanced Data Management Practices
• Implementing Data Governance Frameworks
• Data Quality and Integrity Assurance
• Big Data Analytics and Applications
• Data Security and Ethical Practices
• Risk Management in Data Operations

Course Outlines:

• Day 1: Introduction to Data Management and Business Intelligence
• Introduction to Data Management: Understanding the basic concepts and principles.
• Data Governance: Implementing frameworks for managing data assets.
• Data Quality: Ensuring accuracy, consistency, and reliability of data.
• Data Maturity Assessment: Evaluating the maturity level of data management practices.
• Data Organizational Roles: Defining roles and responsibilities in data management.
• Data Change Management: Managing changes in data processes and systems.
• Day 2: Advanced Data Management
• Data Architecture: Designing the structure of data systems.
• Data Modeling and Design: Creating models to represent data structures.
• Metadata Management: Managing data about data for better understanding and usage.
• Document and Content Management: Organizing and controlling document workflows.
• Day 3: Big Data
• Data Integration: Combining data from different sources.
• Reference and Master Data: Managing critical data entities.
• Data Warehousing and Business Intelligence: Building and using data warehouses for BI.
• Big Data and Data Science: Leveraging big data technologies and data science techniques.
• Day 4: Ethics and Security
• Data Handling Ethics: Ethical considerations in data management.
• Data Storage and Operations: Best practices for storing and operating data.
• Data Security: Protecting data from unauthorized access and breaches.
• Day 5: Data Warehouse Management and Security
• Data Management and Business Intelligence Planning: Developing strategic plans for facility operations.
• Use of Technology and Automation: Enhancing processes with the latest technology.
• Risk Management in Data Management and Business Intelligence: Identifying and mitigating risks.
• Quality Management in Data Management and Business Intelligence: Ensuring high standards in data management.