Introduction to Business Analytics What is business analytics? Types: Descriptive, Predictive, Prescriptive Role in decision-making Real-world applications across industries.
Data Collection & Data Management Data types and sources structured/unstructured Data pipelines and storage Data cleaning and preparation
Introduction to SQL and databases.
Exploratory Data Analysis (EDA) Data visualization techniques Summary statistics Outlier detection and data distributions Tools: Excel, Python (Pandas), Tableau basics.
Statistical Analysis for Business Probability & distributions Hypothesis testing Correlation and regression analysis Statistical significance in business context.
Predictive Analytics & Machine Learning Introduction to machine learning Linear & logistic regression Decision trees, clustering (K-means) Time series forecasting.
Tools & Technologies in Business Analytics Excel Advanced (Pivot tables, Solver) Power BI & Tableau Python (Numbly, Pandas, Matplotlib R basics optional module.
Business Intelligence & Dashboarding Introduction to BI systems Dashboard creation using Power BI/Tableau KPI selection and visualization best practices Automated reporting.
Domain-Specific Analytics Application Marketing analytics (ROI, segmentation) HR analytics (attrition, hiring trends) Financial analytics (risk, forecasting) Supply chain & operations analytics.
Data Ethics, Privacy & Decision-Making Ethical use of business data
Data governance & compliance (GDPR, etc.) Interpreting analytics insights for strategy Communicating results to stakeholders.
Capstone Project & Certification Real-world business analytics project
Team-based or individual Presentation to panel or mentor Certification based on assessment & project.
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