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BCS DA01 Exam Syllabus Topics:

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

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