Quantitative Analysis Courses

Week 1: Advanced Excel for Data Analysis (4 Hours)

Session 1 (2 Hours): Excel Refresher and Introduction to Advanced Features

Quick Review of Basic Excel Functions

Introduction to Advanced Data Functions and Formulas

Managing and Organizing Data in Excel

Session 2 (2 Hours): Data Analysis Techniques in Excel

Data Validation and Conditional Formatting

Advanced Data Analysis with PivotTables and PivotCharts

Introduction to Excel's Data Analysis ToolPak

Week 2: Data Visualization in Excel (6 Hours)

Session 3 (2 Hours): Creating Basic Charts and Graphs

Types of Charts in Excel and When to Use Them

Customizing Charts and Graphs

Best Practices in Data Visualization

Session 4 (2 Hours): Advanced Charting Techniques

Advanced Chart Types (e.g., Waterfall, Sunburst, Histogram)

Dynamic and Interactive Charts

Using Sparklines and Conditional Formatting for Visualization

Session 5 (2 Hours): Dashboard Creation in Excel

Principles of Dashboard Design

Integrating Multiple Data Sources into a Dashboard

Interactive Elements in Dashboards (e.g., Slicers, Form Controls)

Week 3: Advanced Data Manipulation and Analysis (6 Hours)

Session 6 (2 Hours): Utilizing Advanced Excel Functions

Exploring Advanced Functions (e.g., INDEX, MATCH, OFFSET)

Introduction to Array Formulas

Text and Date Functions for Data Preparation

Session 7 (2 Hours): Introduction to Macros and VBA

Basics of Excel Macros for Automation

Introduction to VBA (Visual Basic for Applications)

Simple VBA Scripts for Data Analysis

Session 8 (2 Hours): Solving Real-World Business Problems

Applying Excel Skills to Business Case Studies

Data Analysis Techniques in Real-World Scenarios

Group Exercise on Business Data Analysis

Week 4: Integrating Excel with Other Tools and Capstone Project (4 Hours)

Session 9 (2 Hours): Excel Integration with External Data Sources

Importing and Exporting Data from/to Different Formats

Connecting Excel with Databases and Web Data

Excel and Power BI Integration Basics

Session 10 (2 Hours): Capstone Project and Course Wrap-Up

Final Project: Creating a Comprehensive Business Analysis Report using Excel

Presentation of Capstone Projects

Course Summary and Pathways for Further Learning

Each session should include a mix of theoretical instruction and hands-on exercises, progressively building in complexity. The capstone project should involve a comprehensive task that requires students to apply all the skills they've learned, ideally focusing on a real-world business scenario. This structure ensures that MBA students not only gain technical proficiency in Excel for data analysis and visualization but also understand how to apply these skills in a business context.

Week 1: Introduction to Google Data Studio and Data Visualization (4 Hours)

Session 1 (2 Hours): Fundamentals of Google Data Studio

Introduction to Business Intelligence and Data Visualization

Overview of Google Data Studio: Features and Capabilities

Setting Up and Navigating Google Data Studio

Session 2 (2 Hours): Connecting to Data Sources

Integrating Various Data Sources (Google Sheets, Analytics, SQL databases)

Understanding Data Source Fields and Data Types

Basic Data Transformations and Preparations

Week 2: Building Reports and Visualizations (6 Hours)

Session 3 (2 Hours): Creating Basic Reports and Charts

Designing Reports with Tables, Scorecards, and Basic Charts

Customizing Data Visualization Elements

Best Practices in Report Layout and Design

Session 4 (2 Hours): Advanced Visualization Techniques

Exploring Advanced Chart Types (e.g., Geo Maps, Scatter Charts)

Using Filters and Date Range Controls

Interactive Features in Reports (e.g., Drill Downs)

Session 5 (2 Hours): Enhancing Reports with Styling and Branding

Advanced Styling Options for Professional-Looking Reports

Adding Branding Elements and Custom Themes

Conditional Formatting for Enhanced Data Presentation

Week 3: Advanced Features and Business Applications (6 Hours)

Session 6 (2 Hours): Advanced Data Studio Features

Using Calculated Fields and Custom Formulas

Introduction to Blended Data and Data Joining

Implementing Row-Level Security and Access Controls

Session 7 (2 Hours): Data Exploration and Insights

Exploring Data with Explorer Mode

Using Data Studio for Business Analytics and Insights

Case Studies: Real-World Business Applications

Session 8 (2 Hours): Collaborating and Sharing in Data Studio

Collaborative Features in Google Data Studio

Sharing and Embedding Reports

Best Practices for Managing and Organizing Reports

Week 4: Practical Application and Capstone Project (4 Hours)

Session 9 (2 Hours): Integrating Google Data Studio in Business Strategy

Developing Data-Driven Business Strategies Using Reports

Discussing Ethical Considerations in Data Reporting

Strategies for Effective Data Storytelling in Business

Session 10 (2 Hours): Capstone Project and Course Wrap-Up

Developing a Comprehensive Business Intelligence Dashboard for a Real or Simulated Business Scenario

Presentation of Capstone Projects

Course Summary and Pathways for Further Learning

The course should include a mix of lectures, hands-on exercises, and case studies, with a strong emphasis on practical application using real-world business scenarios. The capstone project in the final week should involve creating a comprehensive business intelligence dashboard, allowing students to apply their learning in a realistic business context. This structure ensures MBA students not only acquire technical skills in Google Data Studio but also understand how to strategically apply these skills for business analysis and decision-making.

Week 1: Advanced Excel for Data Analysis (4 Hours)

Session 1 (2 Hours): Excel Refresher and Introduction to Advanced Features

Quick Review of Basic Excel Functions

Introduction to Advanced Data Functions and Formulas

Managing and Organizing Data in Excel

Session 2 (2 Hours): Data Analysis Techniques in Excel

Data Validation and Conditional Formatting

Advanced Data Analysis with PivotTables and PivotCharts

Introduction to Excel's Data Analysis ToolPak

Week 2: Data Visualization in Excel (6 Hours)

Session 3 (2 Hours): Creating Basic Charts and Graphs

Types of Charts in Excel and When to Use Them

Customizing Charts and Graphs

Best Practices in Data Visualization

Session 4 (2 Hours): Advanced Charting Techniques

Advanced Chart Types (e.g., Waterfall, Sunburst, Histogram)

Dynamic and Interactive Charts

Using Sparklines and Conditional Formatting for Visualization

Session 5 (2 Hours): Dashboard Creation in Excel

Principles of Dashboard Design

Integrating Multiple Data Sources into a Dashboard

Interactive Elements in Dashboards (e.g., Slicers, Form Controls)

Week 3: Advanced Data Manipulation and Analysis (6 Hours)

Session 6 (2 Hours): Utilizing Advanced Excel Functions

Exploring Advanced Functions (e.g., INDEX, MATCH, OFFSET)

Introduction to Array Formulas

Text and Date Functions for Data Preparation

Session 7 (2 Hours): Introduction to Macros and VBA

Basics of Excel Macros for Automation

Introduction to VBA (Visual Basic for Applications)

Simple VBA Scripts for Data Analysis

Session 8 (2 Hours): Solving Real-World Business Problems

Applying Excel Skills to Business Case Studies

Data Analysis Techniques in Real-World Scenarios

Group Exercise on Business Data Analysis

Week 4: Integrating Excel with Other Tools and Capstone Project (4 Hours)

Session 9 (2 Hours): Excel Integration with External Data Sources

Importing and Exporting Data from/to Different Formats

Connecting Excel with Databases and Web Data

Excel and Power BI Integration Basics

Session 10 (2 Hours): Capstone Project and Course Wrap-Up

Final Project: Creating a Comprehensive Business Analysis Report using Excel

Presentation of Capstone Projects

Course Summary and Pathways for Further Learning

Each session should include a mix of theoretical instruction and hands-on exercises, progressively building in complexity. The capstone project should involve a comprehensive task that requires students to apply all the skills they've learned, ideally focusing on a real-world business scenario. This structure ensures that MBA students not only gain technical proficiency in Excel for data analysis and visualization but also understand how to apply these skills in a business context.

Week 1: Introduction to Google Data Studio and Data Visualization (4 Hours)

Session 1 (2 Hours): Fundamentals of Google Data Studio

Introduction to Business Intelligence and Data Visualization

Overview of Google Data Studio: Features and Capabilities

Setting Up and Navigating Google Data Studio

Session 2 (2 Hours): Connecting to Data Sources

Integrating Various Data Sources (Google Sheets, Analytics, SQL databases)

Understanding Data Source Fields and Data Types

Basic Data Transformations and Preparations

Week 2: Building Reports and Visualizations (6 Hours)

Session 3 (2 Hours): Creating Basic Reports and Charts

Designing Reports with Tables, Scorecards, and Basic Charts

Customizing Data Visualization Elements

Best Practices in Report Layout and Design

Session 4 (2 Hours): Advanced Visualization Techniques

Exploring Advanced Chart Types (e.g., Geo Maps, Scatter Charts)

Using Filters and Date Range Controls

Interactive Features in Reports (e.g., Drill Downs)

Session 5 (2 Hours): Enhancing Reports with Styling and Branding

Advanced Styling Options for Professional-Looking Reports

Adding Branding Elements and Custom Themes

Conditional Formatting for Enhanced Data Presentation

Week 3: Advanced Features and Business Applications (6 Hours)

Session 6 (2 Hours): Advanced Data Studio Features

Using Calculated Fields and Custom Formulas

Introduction to Blended Data and Data Joining

Implementing Row-Level Security and Access Controls

Session 7 (2 Hours): Data Exploration and Insights

Exploring Data with Explorer Mode

Using Data Studio for Business Analytics and Insights

Case Studies: Real-World Business Applications

Session 8 (2 Hours): Collaborating and Sharing in Data Studio

Collaborative Features in Google Data Studio

Sharing and Embedding Reports

Best Practices for Managing and Organizing Reports

Week 4: Practical Application and Capstone Project (4 Hours)

Session 9 (2 Hours): Integrating Google Data Studio in Business Strategy

Developing Data-Driven Business Strategies Using Reports

Discussing Ethical Considerations in Data Reporting

Strategies for Effective Data Storytelling in Business

Session 10 (2 Hours): Capstone Project and Course Wrap-Up

Developing a Comprehensive Business Intelligence Dashboard for a Real or Simulated Business Scenario

Presentation of Capstone Projects

Course Summary and Pathways for Further Learning

The course should include a mix of lectures, hands-on exercises, and case studies, with a strong emphasis on practical application using real-world business scenarios. The capstone project in the final week should involve creating a comprehensive business intelligence dashboard, allowing students to apply their learning in a realistic business context. This structure ensures MBA students not only acquire technical skills in Google Data Studio but also understand how to strategically apply these skills for business analysis and decision-making.