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BCS DA01 Braindumps - in .pdf Free Demo

  • Exam Code: DA01
  • Exam Name: BCS Professional Certificate in Data Analysis
  • Last Updated: Aug 23, 2026
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  • Exam Code: DA01
  • Exam Name: BCS Professional Certificate in Data Analysis
  • Last Updated: Aug 23, 2026
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BCS DA01 Exam Syllabus Topics:

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

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