1. Introduction to Data Analytics

• What is Data Analytics & Its Importance
• Types of Data Analytics (Descriptive, Diagnostic, Predictive, Prescriptive)
• Data Life Cycle & Data-Driven Decision Making
• Understanding Data Sources and Formats

2. Advanced Excel for Analytics

• Advanced Formulas & Functions (LOOKUPs, IFs, INDEX-MATCH, etc.)
• Data Cleaning & Transformation Techniques
• Pivot Tables, Pivot Charts & Dashboards
• Conditional Formatting & Data Visualization
• Power Query for Data Import & Automation
• Macros for Workflow Automation

3. SQL for Data Analysis

• Introduction to Databases and SQL Basics
• Data Extraction Using SELECT Queries
• Filtering, Sorting, and Aggregating Data
• Joins, Subqueries & Views
• Data Manipulation (Insert, Update, Delete)
• Real-world Query Scenarios for Reporting

4. Power BI (Business Intelligence & Visualization)

• Connecting to Data Sources & Cleaning Data
• Data Modeling and Relationships
• DAX (Data Analysis Expressions) Functions
• Building Interactive Dashboards & Reports
• Publishing and Sharing in Power BI Service
• Real-World BI Project for Business Insights

5. Python for Data Analytics

• Introduction to Python Programming
• Libraries for Data Analysis: NumPy, Pandas, Matplotlib, Seaborn
• Data Cleaning, Transformation & Aggregation
• Exploratory Data Analysis (EDA)
• Visualization and Reporting with Charts
• Importing Data from Excel, CSV, and SQL Databases

6. Alteryx for Data Preparation

• Introduction to Alteryx Interface & Workflows
• Input/Output Tools & Data Blending
• Data Cleansing, Filtering & Summarizing
• Formula, Join, and Transformation Tools
• Automating Reports and Processes
• Exporting Clean Data for BI Tools

7. Data Visualization & Reporting

• Principles of Data Visualization
• Choosing the Right Chart or Graph
• Designing Professional Dashboards
• Storytelling with Data
• Presentation of Analytical Findings

8. Data-Driven Decision Making

• Understanding KPIs and Metrics
• Data Interpretation & Business Insights
• Predictive vs. Descriptive Analysis
• Real-Time Data Monitoring

9. Data Governance & Ethics

• Data Accuracy, Consistency & Integrity
• Privacy and Security in Data Handling
• Compliance Standards & Best Practices
• Ethical Use of Data

10. Capstone Project

• End-to-End Data Analytics Project
• Using Excel, SQL, Python & Power BI Together
• Data Cleaning → Analysis → Visualization → Insights
• Report Presentation & Final Evaluation