Customer Data Analytics with Excel & PowerBI Course

Course Overview:

This course empowers participants to harness the power of Microsoft Excel and Power BI for effective customer data analysis. By combining these tools, learners will gain insights into customer behavior, segmentation, and predictive modeling.

Module 1: Introduction to Modern Analytics

• Objective: Understand the role of modern analytics in business decision-making.
• Topics Covered:
  • Benefits of modern analytics
  • Ecosystem of modern analytics tools
  • Roles of individuals using these technologies

Module 2: Data Preparation and Cleaning

• Objective: Learn how to clean and transform raw customer data.
• Topics Covered:
  • Importing data into Excel
  • Data cleaning techniques (removing duplicates, handling missing values)
  • Using Power Query for data transformation

Module 3: Exploratory Data Analysis (EDA) in Excel

• Objective: Explore customer data visually and statistically.
• Topics Covered:
  • Descriptive statistics (mean, median, variance)
  • Creating pivot tables and charts
  • Identifying patterns and outliers

Module 4: Customer Segmentation

• Objective: Understand different segmentation methods.
• Topics Covered:
  • RFM (Recency, Frequency, Monetary) analysis
  • K-means clustering
  • Visualizing segments using Power BI

Module 5: Predictive Modeling with Excel

• Objective: Build predictive models for customer behavior.
• Topics Covered:
  • Linear regression for customer lifetime value
  • Logistic regression for churn prediction
  • Model evaluation and interpretation

Module 6: Introduction to Power BI

• Objective: Get acquainted with Power BI’s capabilities.
• Topics Covered:
  • Power BI Desktop vs. Power BI service
  • Connecting to data sources
  • Creating interactive dashboards

Module 7: Visualizing Customer Insights in Power BI

• Objective: Create compelling visualizations for customer data.
• Topics Covered:
  • Building reports and dashboards
  • Custom visuals and slicers
  • Publishing to Power BI service

Module 8: Case Studies and Real-world Applications

• Objective: Apply learned concepts to practical scenarios.
• Topics Covered:
  • Analyzing customer journey data
  • Personalizing marketing campaigns
  • Ethical considerations in data analytics

Assessment:

• Quizzes and hands-on exercises throughout the course

Certification:

• Course completion certificate

Note: The course outline can be adjusted based on the specific requirements of the training participants and the available time