Enterprise Data Model Development
Description
Enterprise data modeling is the set of activities that enables an organization to identify, categorize and define their data assets. An enterprise data model provides the structure around which most data-oriented decisions can be made, including the evaluation of packaged applications, the re-engineering of legacy systems, the development of a data warehouse or other decision support environment.
This course is designed to teach students how to locate, define and represent the data needed by the enterprise. This interactive course provides a combination of lecture and small workshop exercises using a continuing case study that allows the student to grasp and practice the concepts of data modeling on an enterprise scale. It blends basic data modeling activities and concepts with the enterprise view of business data needs. It can be presented using a particular modeling tool or can be taught independent of any modeling tool.
This ICCP-certified course is workshop-focused since design concepts are best learned from doing. The workshops are oriented to solving problems that you have in your current projects. The workshops allow you to learn how the concepts are applied and how to develop skills in data modeling from conceptual, to logical to physical. Additionally, the organization’s chosen data modeling tool can be incorporated into the exercises and training in tool usage can be added to this course.
Objectives
The objectives of the course are to:
- Analyze an enterprise, identifying data components and relationships among them
- Develop the various levels of data models used within an organization
- Determine how to actively engage business people in data modeling
- Model data for the enterprise and represent it via entity-relationship diagrams
- Understand the uses of data models in the enterprise for many initiatives
Seminar Content
- Information as a Enterprise Asset
- Business value of managing data and information
- Definitions
- Enterprise Information Management – Introduction
- What is EIM?
- EIM framework
- EIM goals
- EIM guiding principles
- Issues and challenges of implementing an EIM program
- Key attributes to a successful EIM program
- The EIM organization structure
- Overview of an Enterprise Information Management
- Defining EIM requirements
- Identifying data and meta data sources
- Approaches to EIM implementation – roadmap approach
- Introduction to Enterprise Data Modeling
- Basis for Enterprise Data Modeling – industry best practices and acceptance
- Development of models as part of an enterprise’s business value proposition
- Technical aspects of enterprise data model development
- Success factors for enterprise data modeling
- Challenges and issues in enterprise data modeling
- Staffing the enterprise data model effort
- Credibility
- Representation – business and technical
- Expertise within and outside the team
- Logistics
- Scoping the enterprise data model effort
- Time commitments and durations
- Time-boxing for effective delivery
- Recording the work
- Tool requirements
- Logistics
- Notations, conventions and standards
- Scoping the enterprise
- The organization chart
- Generic functions
- Unique functions
- Enterprise interfaces
- Determining "shared data"
- Input to the modeling effort
- Porter's value chain model
- "Universal" / open-source data models, COTS data models
- Existing internal data models
- Model construction techniques and guidelines
- Modeling concepts and types review
- Names and definitions
- Leveling
- Delineation
- Decomposition
- Achieving consensus
- Subject Area data modeling
- Identifying and defining subject areas
- Subject area relationships
- Conceptual data modeling
- Identifying and defining conceptual entities
- Conceptual entity relationships
- Conceptual entity attributes
- Logical Data Modeling Overview
- Relationship types
- E-R diagrams and how to read them
- Keys in enterprise data modeling
- Normalization for the enterprise
- Patterns in data modeling
- Addressing missing data and data redundancy
- Sub-Entity modeling
- Identifier integrity
- Recursive relationships
- Modeling entity types and subtypes
- How to use the models: How to not be shelf-ware
- Presenting for validation and acceptance
- Dissemination and use
- Data ownership and governance
- Business reference: taxonomy, intranet portal, etc.
- Integration with other components of the IT architecture
- Relationships to more detailed data models
- Implementation for initiatives: data warehousing / business intelligence, re-engineering, enterprise data integration, enterprise resource planning, etc.
- Maintenance
- Integrating enterprise data modeling into an EIM program
- Special Topics in Enterprise Data Modeling\
- Model meta data Supporting multiple business views Data model walkthroughs Reconciling the data model Techniques for effective workshops * Gaining and sustaining management commitment and involvement
- Conclusion
- Workshop Summary, Additional Exercises and Reference Materials
To learn more about how EWSolutions can provide our World-Class Training for your company or to request a quote, please feel free to contact David Marco, our Director of Education at DMarco@EWSolutions.com or call him at 630.920.0005 ext. 103.