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BCS DA01 Exam Syllabus Topics:

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

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