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INFORMATION MANAGEMENT

FUNDAMENTALS & THE DMBOK

TRAINING COURSE OVERVIEW

INFORMATION MANAGEMENT FUNDAMENTALS COURSE | ENTERPR ISE ARCHITECTS © 201 4 2

Information Management Fundamentals Course Objectives: To give participants a solid grounding in all of the core Information Management concepts. Additionally it provides a foundation for students considering DAMA CDMP professional certification

Course Description: This is a 5 day introductory course covering all of the components of Information Management as defined in the DAMA Body of Knowledge (DMBoK)

Course Content: Introduction to the DMBoK: What is the DMBoK, purpose and audience of the DMBoK, changes due in DMBoK 2.0, relationship of DMBoK with other

frameworks (TOGAF / COBIT etc.).

Data Governance: Why Data Governance is at the heart of successful IM, a typical DG reference model, DG roles & responsibilities, the role of the DGO

& its relationship with the PMO.

Data Quality Management: Dimensions of data quality, policies, procedures, metrics, technology and resources for ensuring Data Quality is measured

and ultimately continually improved.

Master & Reference Data Management: The identification and management of Master Data across the enterprise. 4 generic MDM architectures &

their suitability in different cases. MDM maturity assessment to consider business procedures for MDM and the provision and appropriateness of MDM

solutions per major data subject area. How to incrementally implement MDM to align with business priorities.

Data Warehousing & BI Management: Provision of Business Intelligence (BI) to the enterprise and the manner in which data consumed by BI solutions

and the resulting reports are managed. Particularly important if the data is replicated into a Data Warehouse.

Metadata & Models: Provision of metadata repositories and the means of providing business user access and glossaries from these. The

development, use and exploitation of data models, ranging from Enterprise, through Conceptual to Logical and Physical. Maturity assessment considers

the way in which models are utilized in the enterprise and their integration in the Software Development Life Cycle (SDLC).

Data Architecture Management: Approaches, plans, considerations and guidelines for provision of data integration and access. Consideration of Hub

& Spoke, Service-orientated Architecture (SOA), Data Virtualization and assessment of their suitability for the particular use cases.

Data Lifecycle Management: Data is created, read, updated, and archived or deleted. This management function and its maturity assessment

determine how well this is planned for and accomplished.

Data Security & Privacy: Identification of threats and the adoption of defences to prevent unauthorized access, use or loss of data and particularly

abuse of personal data.

Regulatory Compliance: Polices and assurance processes that the enterprise is meeting and adapting to changing legal and regulatory requirements

related to its information and data.

Data Risk Management: Identification of risks (not just security) to data and its use, mitigation, controls and reporting.

Data Management Tools & Repository: Categories & examples of tools, how to select the appropriate toolset, example policy for use of specific

technology to ensure consistency and interoperability across the enterprise.