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BCS DA01 : BCS Professional Certificate in Data Analysis

DA01

Exam Code: DA01

Exam Name: BCS Professional Certificate in Data Analysis

Updated: Aug 07, 2026

Q & A: 0 Questions and Answers

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BCS DA01 Exam Syllabus Topics:

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

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