BCS DA01 : BCS Professional Certificate in Data Analysis

DA01 testking pdf

Exam Code: DA01

Exam Name: BCS Professional Certificate in Data Analysis

Updated: Jul 17, 2026

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DA01 exam dumps

BCS DA01 Exam Syllabus Topics:

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

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