Exam Code: DA01
Exam Name: BCS Professional Certificate in Data Analysis
Updated: Jul 26, 2026
Q & A: 0 Questions and Answers
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The BCS Professional Certificate in Data Analysis certification program provides a comprehensive understanding of data analysis and covers a wide range of topics, including data mining, data visualization, statistical analysis, and predictive modeling. The program is designed to provide participants with practical skills that can be applied in their work environment. The curriculum is structured in a way that ensures that participants get a thorough understanding of the concepts and techniques used in data analysis.
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The DA01 certification program is ideal for professionals who are looking to transition into a career in data analysis or data science. The program is specially tailored for individuals who want to learn how to identify trends, patterns, and relationships in data sets. After completing the program, learners acquire the ability to make data-driven conclusions and devise effective solutions to complex business problems. The BCS DA01 certification is ideal for professionals looking to establish themselves as experts in data analysis or data science.
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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Modelling Data Using Class Diagrams | 35% | - Generalisation - Associations and multiplicity
- Naming conventions - Classes and objects - Aggregation and composition - Class diagrams |
| Topic 2: Analysing Data for Decision-Making | 25% | - Sourcing datasets
- Dataset calculations
- Validating and cleansing datasets
|
| Topic 3: Obtaining and Recording Data | 10% | - Identifying sources of data - Data navigation paths - Data navigation diagrams - CRUD matrix validation |
| Topic 4: Protecting Data | 5% | - Data protection principles - Ethical use of data |
| Topic 5: Defining Data Requirements | 15% | - Data definitions - Metadata
- Relational data theory
- Normalisation
|
| Topic 6: Introduction to Data | 10% | - The data lifecycle - Structured and unstructured data - Initial concepts and terminology
|
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