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BCS DA01 Exam Syllabus Topics:

SectionWeightObjectives
Defining Data Requirements15%- Data definitions
- Relational data theory
  • 1. Two-dimensional structures
    • 2. Primary keys
      • 3. Foreign keys
        • 4. Compound and concatenated keys
          - Metadata
          • 1. Statistical metadata
            • 2. Descriptive metadata
              • 3. Structural metadata
                - Data quality
                - Normalisation
                • 1. Second normal form
                  • 2. Third normal form
                    • 3. Un-normalised form
                      • 4. Third normal form model
                        • 5. First normal form
                          - Domain definitions
                          Introduction to Data10%- Initial concepts and terminology
                          • 1. Information versus data
                            • 2. Data analysis versus data analytics
                              - Data modelling and data models
                              • 1. Static and dynamic views of data
                                • 2. Conceptual, logical and physical data models
                                  - Structured and unstructured data
                                  - The data lifecycle
                                  Obtaining and Recording Data10%- Data navigation diagrams
                                  - Data navigation paths
                                  - Identifying sources of data
                                  - CRUD matrix validation
                                  Protecting Data5%- Ethical use of data
                                  - Data protection principles
                                  Modelling Data Using Class Diagrams35%- Classes and objects
                                  - Aggregation and composition
                                  - Associations and multiplicity
                                  • 1. Many-to-many relationships
                                    • 2. One-to-one relationships
                                      • 3. One-to-many relationships
                                        • 4. Multiple roles
                                          • 5. Resolving many-to-many relationships
                                            - Naming conventions
                                            - Class diagrams
                                            - Generalisation
                                            - Attributes
                                            Analysing Data for Decision-Making25%- Interpreting results
                                            - Sourcing datasets
                                            • 1. Data lineage
                                              - Data analytics process
                                              - Dataset calculations
                                              • 1. Probability
                                                • 2. Median
                                                  • 3. NULL values
                                                    • 4. Mode
                                                      • 5. Mean
                                                        • 6. Totalling
                                                          • 7. Maximum and minimum
                                                            • 8. Counting
                                                              - Identifying meaningful relationships
                                                              • 1. Regression analysis
                                                                • 2. Correlation and causation
                                                                  • 3. Time-series analysis and forecasting
                                                                    - Validating and cleansing datasets
                                                                    • 1. Confirmation bias
                                                                      • 2. Sampling
                                                                        • 3. Outliers
                                                                          • 4. Consistency

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