BUSINESS ANALYTICS

MODULES:

• Introduction to Business Analytics and Data Basics
• Overview of Business Analytics: Definition and Importance
• Types of Business Analytics: Descriptive, Predictive, and Prescriptive Analytics
• Case Studies: Real-world examples of successful business analytics implementations
• Basics of Data: Structured vs. Unstructured Data
• Introduction to Data Sources: Internal and External Data
• Data Collection and Data Cleaning: Importance and Techniques
• Data Exploration and Visualization
• Tools for Data Visualization: Introduction to tools like Tableau or Power BI
• Introduction to Excel for Business Analytics
• Basic Statistical Concepts for Business Analysis
• Hands-on Exercise: Analyzing data in Excel

• Day 2: Advanced Analytics and Predictive Modeling
• Overview of Advanced Analytics
• Introduction to Predictive Modeling
• Common Predictive Modeling Algorithms
• Hands-on Exercise: Building a Predictive Model using Python or R
• Model Evaluation and Validation
• Introduction to Machine Learning for Business Analytics
• Applications of Machine Learning in Business
• Case Studies: Successful Applications of Predictive Analytics
• Q&A and Discussion on Challenges in Implementing Predictive Analytics

Day 3:

• Decision Support Systems and Business Intelligence
• Introduction to Business Intelligence (BI).
• Data Warehousing: Basics and Importance.
• Overview of Decision Support Systems (DSS)
• BI Tools: Overview of tools like SAP BusinessObjects, IBM Cognos
• Hands-on Exercise: Building a Dashboard in a BI Tool
• Ethical Considerations in Business Analytics
• Future Trends in Business Analytics