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BCS DA01 Exam Syllabus Topics:

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

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