Golad Academy · Course syllabus
Data Analysis
- Duration
- 12 weeks
- Skill level
- Beginner to Intermediate
- Next cohort
- 1 March 2027
- Course price
- £99
Overview
The Data Analysis course gives learners the practical skills to collect, clean, analyse and present data. Using Excel, business intelligence tools and core statistics, you will learn to turn everyday data into clear insights and recommendations for decision-makers in business, health, education and government. Designed for beginners, it requires no programming experience.
Format: Live online classes + GADLE
Learning outcomes
- Collect, validate and clean data from surveys, databases and spreadsheets
- Use advanced Excel: lookups, PivotTables and dynamic dashboards
- Build interactive reports in a business intelligence tool
- Apply core statistics and probability to everyday decisions
- Write executive summaries and present findings to stakeholders
- Complete an end-to-end portfolio project
Curriculum
Module 1: Introduction to Data Analytics
- What is Data Analysis? Importance in Decision-Making
- Types of Data Analysis: Descriptive, Diagnostic, Predictive, Prescriptive
- Overview of The Data Analytics Lifecycle: Collection → Cleaning → Analysis → Storytelling
- Real-World Applications: Business, Health, Governance, Education
Module 2: Data Collection & Management
- Data Sources: Surveys, Databases, Reports, CSV/Excel Files
- Ethical Considerations and Privacy in Data Collection
- Data Validation and Entry Standards
- Organizing and Storing Data for Analysis
Module 3: Data Cleaning & Preparation
- Handling Missing Data, Duplicates, and Outliers
- Formatting and Standardizing Data (Dates, Text, Categories)
- Simple Transformations: Sorting, Filtering, Grouping
- Introduction to Data Quality Checks
Module 4: Exploratory Data Analysis (EDA)
- Summary Statistics: Mean, Median, Mode, Range, Standard Deviation
- Visual Exploration: Charts, Graphs, Tables
- Identifying Patterns, Trends, and Anomalies
- Basic Correlation and Relationships Between Variables
Module 5: Data Visualization Principles
- Best Practices for Presenting Data Effectively
- Choosing the Right Chart Type: Bar, Line, Pie, Scatter, Heatmaps
- Storytelling with Visuals for Decision-Making
- Infographics and Dashboard Design Principles
Module 6: Advanced Excel for Data Analysis
- Lookup and Reference Functions: VLOOKUP, HLOOKUP, INDEX-MATCH
- PivotTables, PivotCharts, and Dynamic Dashboards
- Conditional Formatting and Custom Calculations
- Scenario Analysis and Simple Forecasting
Module 7: Introduction to Business Intelligence (BI)
- Understanding BI and Its Role in Organizations
- BI Tools for Non-Technical Users
- Creating Interactive Dashboards and Visual Reports
- Connecting Data Sources for Analysis
Module 8: Statistical Concepts for Decision-Making
- Descriptive vs Inferential Statistics
- Probability Basics and Distributions
- Introduction to Hypothesis Testing
- Interpreting Results for Business Insights
Module 9: Data Storytelling & Reporting
- Translating Data into Actionable Insights
- Writing Executive Summaries and Visual Reports
- Creating Presentations for Stakeholders
- Communicating Trends, Patterns, and Recommendations
Module 10: Domain-Specific Applications
- Healthcare: Patient Data Trends, Program Evaluation
- Education: Enrollment Statistics, Performance Analysis
- Business: Sales, Marketing, and Operational KPIs
- Governance: Public Data Monitoring, Program Performance
Module 11: Capstone Project & Portfolio Building
- Capstone: End-to-End Data Analysis Project
- Apply Full Pipeline: Data Collection → Cleaning → Visualization → Insights
- Present Findings in a Written Report and Interactive Dashboard
- Build a Portfolio for Career
Module 12: Career Workshop & Next Steps
- Resume Building for Data Analysis Roles
- LinkedIn Branding and Online Portfolio Strategies
- Interview Preparation: Explaining Analysis and Insights
- Continuing Education: Certifications and Learning Paths
Industry-extension modules (optional, on GADLE)
- SQL for Analysts — Relational databases and tables; SELECT, WHERE, ORDER BY and aggregation; JOINs across related tables; Using SQL as a data source for dashboards
- Automating Reports — Power Query for repeatable data preparation; Scheduled refresh and shared dashboards; Data validation and error checks; Documenting your reporting process
Tools
Microsoft Excel, Power Query, Power BI, Tableau, Google Sheets, Looker Studio, PowerPoint, SQL basics
Prepares you for
- Microsoft PL-300: Power BI Data Analyst (foundation)
- Microsoft Office Specialist: Excel Expert
- Google Data Analytics Professional Certificate
Career paths
Data Analyst, Reporting / MI Analyst, Business Intelligence Assistant, Monitoring & Evaluation Analyst, Operations Analyst, Research Assistant
What you’ll gain
Confident Decision-Making · Clear Reporting · Time Saved Through Automation · Career Opportunities