Certified Data Analyst (CDA)
Advance your career and master the skills required to excel in the modern digital economy with our industry-recognized certification program.
Certification Overview
The Certified Data Analyst (CDA) certification is an applied, entry-to-mid-level program that prepares participants to collect, clean, analyze, visualize, and communicate data to inform decision-making. Whether you're starting your career in analytics or upskilling into a more data-driven role, this program offers the foundational tools and workflows required in today’s business environments.
This program blends real datasets, tools training, guided labs, and mini-projects.
Certificate Description
Duration: 2–3 months (flexible pace, project-based)
Target Audience
Beginners in data or business analytics
Fresh graduates and entry-level professionals
Administrators and officers seeking data skills
Finance, marketing, HR, and operations staff aiming to upskill
NGO and government staff handling reporting or M&E data
Benefits of Attending
Master core analytics tools used in the job market
Build dashboards and analytical reports
Clean, analyze, and interpret data for decision support
Create a portfolio of business-focused data projects
Prepare for data analyst roles across sectors
Certification Objectives
Understand the role and workflow of a data analyst
Perform data cleaning, transformation, and exploration
Use SQL to query databases and summarize information
Build interactive dashboards using Power BI or Tableau
Generate insights and communicate them effectively
Certification Assessment
Module Quizzes: Tool and concept mastery checks
Mini-Projects: Applied tasks with real-world datasets
Capstone Project: Analyze, visualize, and report on a dataset of choice
Presentation: Dashboard walkthrough + insights briefing
Portfolio: Submission of Excel, SQL queries, Python notebook, and BI dashboard
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Our admissions team is available to answer any questions about the curriculum or enrollment process.
Contact AdmissionsCourse Modules
Module 1: Fundamentals of Data Analysis and Excel for Analytics
- What is data analysis? Key roles and concepts
- Excel functions for analysis: VLOOKUP, IF, INDEX/MATCH, pivot tables
- Cleaning and formatting data in Excel
- Creating reports and charts
- Hands-on Exercise: Analyze a Sales Dataset in Excel
- Case Study: Regional Sales Reporting for FMCG Company
Module 2: SQL for Data Analysts
- Database concepts and structure
- SQL queries: SELECT, WHERE, JOIN, GROUP BY, HAVING
- Aggregation and filtering for business reporting
- Creating views and basic stored procedures
- Hands-on Exercise: Query an Orders and Customers Database
- Case Study: Customer Retention Report for E-Commerce
Module 3: Python for Data Wrangling and Analysis
- Introduction to Python for analytics (pandas, numpy)
- Importing data (CSV, Excel, APIs)
- Cleaning, transforming, and summarizing datasets
- Basic visualizations with matplotlib and seaborn
- Hands-on Exercise: Analyze HR Attrition Data with Pandas
- Case Study: Monthly Employee Retention Analytics
Module 4: Data Visualization and Dashboards
- Principles of effective visual communication
- Power BI/Tableau basics: data import, calculated fields, filters
- Interactive visuals, slicers, and storytelling dashboards
- Sharing and publishing reports
- Hands-on Exercise: Build a Sales Dashboard in Power BI
- Case Study: Budget Monitoring Dashboard for NGO Program
Module 5: Business Insights and Communication
- Framing business questions and KPIs
- Insight generation and recommendation writing
- Presenting findings to technical and non-technical audiences
- Creating executive summaries and visual reports
- Hands-on Exercise: Draft a Business Insights Report
- Case Study: Campaign Performance Analysis for Marketing Team