Synopsis
This business data modeling training course explores business rules, policies and procedures and how they can be modeled effectively. Participants will learn entity relationship diagramming, super and sub-types, attributive and associative entities, and documenting data constraints. The course's logical data modeling approaches focus on the important requirements of the business that are discovered through significant user involvement during the analysis phase. You will also learn how to create models without being limited by technology or organizational structure.
The ability to communicate the intersection of business processes and information/data needs is key to the success of any software development project. Understanding and explaining user needs is a major challenge and opportunity for the business analyst. The business analyst who understands structured modeling has a distinct advantage in addressing and communicating requirements. And the use of models can greatly increase all stakeholders’ understanding of the relevancy of business rules and data management requirements to the project at hand.
Reminder: Prior to taking this course, we recommend that you have acquired the background as taught in Eliciting and Managing Requirements.
This course is aligned with version 3.0 of A Guide to the Business Analysis Body of Knowledge® (BABOK® Guide)™.
Learn
- Explain how a lack of effective data analysis and usage can affect the risk exposure, cost control, and profitability of your organization
- Explain the role of the business analyst in gathering data-related requirements from stakeholders
- Create, communicate, and validate conceptual data models with your business stakeholders
- Create normalized logical data models as a hand-off to solution delivery
Topics
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Applying Logical Data Models
- Associative entities
- Data constraints
- Using logical data models
- Analysis of organizational and geographical data distribution
- Supporting the organizational data standards
- Software acquisition
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Business Data and Governance
- Data Governance
- Data Management Functions
- Data Governance vs. IT Governance
- Data Management Roles
- Business Analysis and Data Management
- The Value of Data to the Organization
- Data Management and Risk
- Data, Costs, and Revenue
- Data Quality
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Business Data Modeling Workshop
- Put what has been learned into practice
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Conceptual Data Models
- System development challenges
- Data requirements
- Models and modeling
- Data, information and knowledge
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Data Normalization
- Normalization and forms
- The physical data model
- Reverse engineering
- The database designer
- Denormalization
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Data Relationships
- Naming standards for relationships
- Relationship cardinalities
- Relationships affected by time
- Modeling time-dependent data
- The importance of definitions
- Alternative notations
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Logical Data Models
- Entity types
- Subtyping
- Attributive entities and multivalued attributes
- Nondependence
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Verifying and Validating Data Models
- Internal verification
- Presenting data diagrams
- Dos and don'ts of presenting data diagrams