The CPDA certification equips candidates with the comprehensive skills required to navigate the full data analytics lifecycle. From foundational techniques in data management and statistical analysis to advanced methods in data visualization, business intelligence dashboards, and predictive modeling, candidates develop the capabilities needed to convert raw data into actionable insights. The certification is structured around four core parts—Data Analyst Foundation, Data Visualization, Business Intelligence, and Predictive Analytics-ensuring a well-rounded and industry-relevant skill set. This certification validates a professional's ability to apply analytical techniques effectively and drive data-informed decision-making across a range of business contexts.
Part 1 (40%)
Data Analytics Foundation
Foundational Skills in Python
Data Management Techniques
Statistical Foundations
Inferential Analyses
Basic Regression Concepts
ETL Awareness
Tools & Libraries
Robust Data Handling
Part 2 (15%)
Data Visualisation
Principles of Effective Visualization
Python Visualization Tools
Storytelling with Data
Ethical Data Presentation
Excel Visualization
Interactive Dashboards
Focus on Decision-Making
Adaptation to Various Tools
Part 3 (15%)
Business Intelligence
Foundations of BI
Microsoft Power BI
Data Integration
Dynamic Dashboards
DAX and Advanced Calculations
Performance Optimization
Excel for BI
Strategic Impact
Part 4 (30%)
Predictive Analytics
Regression & Classification Basics
Model Assumptions & Diagnostics
Multicollinearity Solutions
Handling Categorical Predictors
Ordinal & Multinomial Outcomes
Model Validation Techniques
Performance Metrics
Real-World Deployment
CPDA™ Certification Exam Structure
To earn the Certified Professional in Data Analytics (CPDA) designation, candidates must successfully complete two online proctored examinations: a knowledge-based exam and a practical application exam.
Exam A: Test of Knowledge
This online proctored exam assesses a candidate’s theoretical understanding and applied knowledge across the data analytics domain. It includes multiple-choice, multi-select, and true/false questions. The exam duration is 120 minutes, and a minimum score of 70% is required to pass.
Exam B: Practical Application
Also delivered as an online proctored assessment, this exam presents candidates with realistic business scenarios and datasets. Candidates must demonstrate their ability to apply the data analytics lifecycle, analyze complex data, and communicate findings clearly. The exam duration is 180 minutes, and a minimum score of 85 out of 150 marks is required to pass.