Synopsis
The Business Data Modelling 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 modelling approaches focus on the important requirements of the business that are discovered through significant user involvement during the analysis phase. Delegates will also learn how to create models without being limited by technology or organisational 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 modelling 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 delegates 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 organisation
- 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 normalised 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 organisational and geographical data distribution
Supporting the organisational 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 Organisation
Data Management and Risk
Data, Costs, and Revenue
Data Quality
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Business Data Modelling Workshop
Put what has been learned into practice
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Conceptual Data Models
System development challenges
Data requirements
Models and modelling
Data, information and knowledge
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Data Normalisation
Normalisation and forms
The physical data model
Reverse engineering
The database designer
Denormalisation
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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
Sub-typing
Attributive entities and multi-valued attributes
Non-dependence
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Verifying and Validating Data Models
Internal verification
Presenting data diagrams
Dos and don'ts of presenting data diagrams
