Data Management Professional Certification

What are the Goals?

This training course provides a solid foundation across the entire Information Management spectrum.

By attending the course, participants will effectively be able to:

• Understand the importunate and application of “information management professionalism”
• Learn the professional management techniques to address business challenges
• Explore the data Management and architecture frameworks
• Recognize the vital roles of Master Data Management and Data Governance
• Apply professionally the best practices for managing Enterprise Information needs

Who is this Training Course for?

Data Management professional certification training program is essential for everyone needs to be capable, knowledgeable, and expert in his field. This course is suitable to a wide range of professionals in Information Management, Data Governance, Master Data Management and Data Quality initiatives, but will greatly benefit:

• Data Analyst
• Database administrators
• Information Managers & Architects
• Data Governance Managers
• Data Quality Managers
• Business Analysts
• Executives Management
• Technology Leaders
• Software engineers
• Any professional involved in Data Analytics

Daily Agenda

Day One: The Data Management Process, and Overview of the Certification 

• Overview of the certificate and its exam
• Data management as a discipline
• The purpose and scope of the DAMA International Data Management 
• Data Management drivers, benefits, and potential pitfalls
• Enterprise Data Management Framework
• Data Management Function

Day Two: Data Governance & Data Quality Management 

• The role of the Data Governance in successful Data Management
• Key topic of Data Ethics & Compliance.
• Understand the various Data Quality areas
• Explore Data Quality policies and procedures
• Linking Data Quality with other data disciplines
• The major components to leverage reference and master data

Day Three: Data Warehouse, BI, Modeling & Metadata Management

• Concept of Data warehousing & Business Intelligence (BI) management
• Types of data warehouse and BI platforms
• The fundamentals of Big Data
• Features of Data Modeling
• The differences between data and metadata usage, and implementation of metadata

Day Four: Data Architecture and Lifecycle Management, Data Security Management 

• The important types of architectures and proactive planning
• The data value chain
• Differences between lifecycles and systems development
• The key goals of Data Security Management
• Risk assessment & monitoring, of Data Security Management
• Effective Document and Content Management 

Day Five: Data Storage and Operations Management & Data Integration and Interoperability 

• The effective Data Storage’s components and Operations Management
• Data Technology Management
• Roles and responsibilities
• Data, I&I practices, and the best solutions
• Data interchange & data replication
• Aligning within Data Governance and expanded Data Management activities