WEEK 1: Business Analytics Foundations (Days 1–7)

📍 Day 1 — Introduction to Business Analytics

• What is Business Analytics?

• Types: Descriptive, Predictive, Prescriptive

📍 Day 2 — Business Problems to Data Problems

• How business questions translate into analytical questions

• Framing hypotheses

📍 Day 3 — Data Types and Data Sources

• Structured vs Unstructured Data

• Primary vs Secondary data sources

📍 Day 4 — Excel Basics for Analytics

• Formulas, Conditional Formatting, Sorting/Filtering

• Introduction to Pivot Tables

📍 Day 5 — Data Cleaning and Preparation

• Handling missing values

• Removing duplicates

• Basic data wrangling (Excel)

📍 Day 6 — Introduction to SQL for Analysts

• SELECT, WHERE, ORDER BY

• Simple Queries to fetch business insights

📍 Day 7 — Mini Project 1

• Analyze a sales dataset (Excel + SQL):

  • Total Revenue

  • Best-selling product

  • Revenue by region

WEEK 2: Analytics Techniques and Visualizations(Days 8–14)

📍 Day 8 — Basic Statistics for Business

• Mean, Median, Mode

• Variance, Standard Deviation

📍 Day 9 — Exploratory Data Analysis (EDA)

• Identify trends and patterns

• EDA on Excel dataset

📍 Day 10 — Data Visualization Concepts

• Importance of visuals in business

• Charts: Bar, Pie, Line, Histogram

📍 Day 11 — Building Dashboards in Excel

• Slicers, Pivot Charts, KPI Cards

📍 Day 12 — Introduction to Power BI / Tableau

• Connecting to data

• Basic dashboard creation

📍 Day 13 — Business Case Study 1

• Example: Analyze Customer Churn data

• Identify key drivers of churn

📍 Day 14 — Mini Project 2

• Build a Customer Sales Dashboard (Power BI / Excel)

WEEK 3: Advanced Techniques, Reporting, and Decision Making (Days 15–21)

📍 Day 15 — Predictive Analytics Basics

• Regression, Classification intro

• Concept of forecasting

📍 Day 16 — Introduction to Python for Analysts

• Setting up Python

• Simple Pandas operations (optional but powerful)

📍 Day 17 — Business Storytelling with Data

• How to present findings to non-technical stakeholders

• Building a compelling report deck

📍 Day 18 — A/B Testing and Business Experimentation

• What is A/B Testing?

• Simple example: Website button color test

📍 Day 19 — Metrics and KPIs for Different Industries

• Marketing: CTR, CPA, ROI

• Retail: Conversion Rate, Average Order Value

• SaaS: MRR, Churn Rate

📍 Day 20 — Career Paths in Business Analytics

• Business Analyst vs Data Analyst vs Data Scientist

• Certifications and further learning (Google, IBM, etc.)

📍 Day 21 — Final Capstone Project

• Full Business Analysis Report:

  • Choose a public dataset

  • Perform data cleaning, EDA, visualization

  • Write business insights and recommendations