BCS DA01 Exam Details & Actual Exam Questions

  • Exam Code/Number: DA01
  • Exam Name/Title: BCS Professional Certificate in Data Analysis
  • Certification Provider: BCS
  • Corresponding Certification: BCS Other Certification
  • Certification Level: Professional / Intermediate

BCS Professional Certificate in Data Analysis Exam Questions

We are already working hard to make DA01 exam material available to our valued customers. If you are interested in DA01 exam material, provide us your email and we will notify you.

BCS DA01 Exam Overview:

Certification Vendor:BCS, The Chartered Institute for IT
Exam Name:BCS Professional Certificate in Data Analysis
Exam Number:DA01
Real Exam Qty:40
Exam Format:Scenario-based, Multiple-choice, Closed-book
Exam Price:£360 (UK), varies by region
Passing Score:65%
Available Languages:English
Exam Duration:90 minutes
Certificate Validity Period:Valid for life (no renewal required)
Related Certifications:BCS Advanced Diploma in Business Analysis
BCS International Diploma in Business Analysis
Recommended Training:Official Syllabus PDF
BCS Approved Training Providers
Exam Registration:BCS Official Registration
Pearson VUE Booking
Exam Way:Onsite at Pearson VUE test centres or online remote proctored
Pre Condition:No mandatory prerequisites; knowledge equivalent to BCS International Business Analysis Diploma recommended
Official Syllabus URL:https://www.bcs.org/qualifications-and-certifications/certifications-for-professionals/business-analysis/professional-certificate-in-data-analysis/

BCS DA01 Exam Syllabus Topics:

SectionWeightObjectives
Introduction to Data10%- Definitions: data, data analysis, model, information, business intelligence
- Context and purpose of data analysis
Defining Data Requirements15%- Metadata and domain definitions
- Data quality characteristics
- Data rationalisation
Obtaining and Recording Data10%- CRUD matrix validation
- Data sources and sampling methods
- Data navigation paths
Data Protection and Ethics10%- Legal and regulatory requirements
- Ethics in data usage
- Data security and privacy principles
Analysing Data for Decision-Making25%- Analysis techniques and interpretation
- Data visualisation and reporting
- Data validation, outliers, bias, consistency
Validation and Verification10%- Review and verification processes
- Model validation techniques
Data Modelling Concepts20%- Data normalisation: 1NF, 2NF, 3NF, keys
- Class diagrams, attributes, relationships, generalisation
- Entity relationship modelling


0
0
0
10