Grasp the fundamentals of business analytics and explore its real-world applications. Learn about different data types, their sources, and the significance they hold in driving informed decisions
- Introduction to Business Analytics
- Various domain applications of Business Analytics
- Importance of data in business and types of data
- Sources of Data
- Structured vs. Unstructured Data
Master advanced Excel functions and tools to perform efficient data analysis and modeling. Build expertise in data connections, summarization, and preprocessing while gaining hands-on proficiency with Power Pivot and Power Query for robust data modeling. Explore advanced techniques such as what-if analysis and Excel’s toolpacks and add-ins to enhance decision-making capabilities.
- Excel Formulas and Functions (Sumif, Countif, Averageif, Ifelse, Ifelse with AND/OR)
- Data Connections (Web connections in Excel, Database connections in Excel)
- Data Summarization (Using Pivot Tables)
- Data Modelling (Power Pivot)
- Data Preprocessing (Power Query: importing, cleaning, transforming data, custom columns)
- Advanced Excel Functions (Sumifs, Countifs, Averageifs, TEXT, Vlookup, Introduction to Xlookup)
- Data Analysis ToolPak (enabling and using the toolpack, Correlation feature demo)
- What-if Analysis (Scenario Manager, Goal Seek, Solver demos)
- Advanced Excel Add-ins (Real Statistics Resource Pack)
Gain practical expertise in Power BI for data cleaning, visualization, and modeling. Create advanced dashboards, optimize performance, and collaborate seamlessly on interactive reports.
- Introduction to Power BI and its features
- Best practices in Data visualization
- Data cleaning, shaping, and modelling in Power Query
- Advanced visualizations and interactive report features
- Publishing, sharing, and collaborating on Power BI reports
- Performance optimization and advanced data modelling techniques
Understand the principles of predictive modeling and apply them to real-world scenarios. Build, evaluate, and interpret regression and classification models with confidence.
- Concept of Predictive Models
- Classification vs. regression models
- Understanding R Square, RMSE, and standard errors
- Building and interpreting regression models (SLR and MLR)
- Building binary classification models using logistic regression
- Concept of confusion matrix
Learn how to apply analytics across marketing, HR, and finance to solve business challenges. Develop hands-on skills in customer segmentation, market modeling, and predictive analysis, while leveraging Excel for data-driven insights and model building.
- Marketing Analytics:
- Introduction to marketing analytics and its importance
- Customer segmentation and market mix modelling
- Market basket analysis and practical exercises in Excel
- HR Analytics:
- Introduction to HR analytics and its transformative role
- Applied HR analytics: regression and classification models
- Predictive analytics for attrition rate, employee CTC, and workforce planning
- Financial Analytics:
- Introduction to Financial Analytics
- Applications in fraud detection, customer profiling, and creditworthiness
