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Data Science

Business Analytics

Steppingstone to the world of Microsoft Cloud

Course Overview

Welcome to Business Analytics!
This course introduces the core concepts of Business Analytics, equipping you with the skills to analyze data and make informed decisions. From data collection to advanced analysis, you’ll gain hands-on experience with essential tools and techniques. Get ready to leverage data for business success!

  • Objective: Provide a foundational understanding of Business Analytics and data-driven decision-making.

 

Week 1: Introduction to Business Analytics

      Overview of Business Analytics:

  • What is business analytics? Importance in decision-making
 

      Types of analytics:

  • Descriptive, Diagnostic, Predictive, and Prescriptive
 

      The Analytics Process:

  • Data collection, preparation, analysis, and reporting
 

      Tools of Business Analytics:

  • Introduction to Excel, Google Sheets, and BI tools (Power BI, Tableau)
 

Week 2: Understanding Data Types and Data Collection

      Types of Data:

  • Structured vs. Unstructured Data
  • Quantitative vs. Qualitative Data
 

      Data Sources:

  • Internal vs. External data
  • Primary vs. Secondary Data
 
      Data Collection Methods:

  • Surveys, interviews, databases, APIs, web scraping
 

Week 3: Data Cleaning and Data Preparation

      Importance of Data Cleaning:

  • Handling missing data, duplicates, outliers, and inconsistencies
  • Cleaning techniques in Excel (filtering, sorting, removing duplicates)
 

      Data Transformation:

  • Normalization, aggregation, and feature engineering
 

      Hands-on Activity:

  • Data cleaning using a sample dataset in Excel
 

Week 4: Introduction to Data Visualization

      Why Data Visualization Matters:

  • Importance of visualization in decision-making and storytelling
 

      Types of Visualizations:

  • Bar charts, pie charts, line graphs, scatter plots, histograms
 

      Principles of Effective Visualization:

  • Clear, simple, and visually appealing graphics
 

      Tools for Visualization:

  • Introduction to Excel charting tools and Google Sheets
 

      Hands-on Activity:

  • Create simple charts and graphs in Excel
 

Week 5: Descriptive Analytics and Summary Statistics

      Understanding Descriptive Analytics:

      Measures of central tendency: Mean, Median, Mode

      Measures of dispersion: Range, Variance, Standard Deviation

       Exploratory Data Analysis (EDA):

  • Using EDA to summarize and visualize data distributions
 

     Hands-on Activity:

  • Calculate descriptive statistics in Excel and create basic visualizations
 

Week 6: Predictive Analytics and Introduction to Regression

      What is Predictive Analytics?

  • Overview of forecasting and prediction in business analytics
 

      Introduction to Regression Analysis:

  • Basic understanding of linear regression
  • Dependent and independent variables 
 
      Building Predictive Models in Excel: 
 
  •  Introduction to Excel’s regression tools
 
      Hands-on Activity: 
 
  • Implementing a simple linear regression model in Excel
 

Week 7: Intermediate Data Visualization

      Advanced Visualizations: 

  • Creating dashboards and interactive visualizations 
  • Visualization techniques for large datasets
 

      Tools for Data Visualization: 

  • Introduction to Power BI or Tableau (basic overview) 
 
      Hands-on Activity: 
 
  •  Creating a basic dashboard in Excel or Google Sheets
 

Week 8: Data Analytics for Business Decisions

      How Analytics Supports Business Decisions: 

  • Key metrics for decision-making in business (KPIs, ROI, NPV) 
  • How analytics drives business performance
 

      Case Studies: 

  • Real-world examples of data-driven decision-making
 
      Hands-on Activity: 
 
  • Analyze a business case using descriptive and predictive analytics 
 

Week 9: Introduction to SQL for Data Querying

      What is SQL and Why It’s Important for Analytics: 

  • Basic concepts of databases and SQL
  • SQL syntax overview: SELECT, WHERE, JOIN, GROUP BY
 

      Using SQL to Query Databases: 

  • Querying datasets for insights
 
     Hands-on Activity: 
 
  • Writing basic SQL queries to extract data from a sample database
 

Week 10: Introduction to Data Mining and Clustering

     What is Data Mining? 

  • Techniques for uncovering patterns and trends in data 
  • Overview of Classification, clustering, and association  
 

     Clustering Techniques: 

  • Introduction to K-Means clustering for market segmentation
 
    Hands-on Activity: 
 
  • Simple clustering example using Excel or Google Sheets
 

Week 11: Predictive Modeling with Machine Learning

     Overview of Machine Learning: 

  • Understanding the role of machine learning in predictive analytics
  • Types of machine learning: Supervised vs. Unsupervised
 

     Hands-on Introduction to ML Tools:

  • Querying datasets for insights
 
     Hands-on Activity: 
 
  • Implementing a simple Classification model using a sample dataset
 

Week 12: Prescriptive Analytics and Optimization

      What is Prescriptive Analytics?

  • Prescriptive vs. Predictive analytics: Decision optimization
 

     Introduction to Optimization Techniques:

  • Linear programming and decision analysis
 

     Real-World Applications:

  • Prescriptive analytics in supply chain management, resource allocation
 
     Hands-on Activity: 
 
  • Simple optimization problem solved in Excel
 

Week 13: Prescriptive Analytics and Optimization

      Objective:

  • Hands-on workshop to build a comprehensive business analytics dashboard 
 

     Tasks:

  • Use Excel or Power BI/Tableau to create a dashboard for business insights  

 

     Collaboration:

  • Work in groups to build a dashboard that includes key metrics and visualizations 
 
      Feedback and Discussion:
 
  •  Review and critique dashboards, offering improvement suggestions  
 

Week 14: Workshop 2: Predictive Modeling and Forecasting

      Objective:

  • Hands-on workshop on building predictive models for business forecasting
 

      Tasks:

  • Use Excel or another tool to implement regression models for sales forecasting or demand
    planning 
     

 

      Collaboration:

  • Work in pairs or groups to solve real-world forecasting problems
 
      Feedback and Discussion:
 
  •  Present models and discuss improvements and applications 
 

Week 15: Workshop 3: Customer Segmentation Using Clustering

     Objective:

  • Hands-on workshop to apply clustering techniques for customer segmentation  
 

     Tasks:

  • Use K-Means clustering to segment a customer dataset based on purchasing behavior
 

     Collaboration:

  • Work in small groups to identify key customer segments
 
      Feedback and Discussion:
 
  •  Present results and discuss how to leverage segmentation for marketing strategies
 

Week 16: Workshop 4: Data-Driven Business Strategy Development

      Objective:

  • Hands-on workshop to develop data-driven strategies for a business case 
 

      Tasks:

  • Create a business strategy using analytics (KPIs, data analysis, predictive models)
 

     Collaboration:

  • Work in teams to create a comprehensive data-driven strategy and presentation
 
       Feedback and Final Discussion:
 
  •  Present strategies to the class, with feedback from instructors and peers
 

      Tools and Software Used:

  •  Excel/Google Sheets: For data analysis, cleaning, and visualization
  •  Power BI/Tableau: For data visualization and dashboards
  •  SQL: For database querying
  • Google Colab or Python (Optional): For basic machine learning models
  • Basic Data Analytics Tools: R or Python can be introduced briefly depending on class progression
 
 

FAQ

This course is specifically designed for school students who want to gain an understanding of Business Analytics.
Basic knowledge of data analysis and statistics is required. Our Introduction to Business Analytics will help you get ready for this course.

The course is tailored for middle and high school students. However, any enthusiastic learner interested in the subject is welcome to join.

All you need is a computer with internet access. We will provide any necessary software and materials as part of the course.

Yes, upon successful completion of the course, you will be awarded a certificate. This certificate recognizes your understanding of Business Analytics..

Enrollment is simple! Choose the course, and follow the enrollment instructions. If you encounter any issues, our support team is ready to assist you.

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Instructor:
Gaurav

Business Analytics​ Expert

About This Course:

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