Introduction to Data Analytics for Business

Who Should Attend?


Duration: 1 Day

This course prepares business professionals to gain competitive advantages with commonly available enterprise data from applications like CRM, ERP, POS, etc. By having the right approach and applying the relevant techniques, these datasets can be used for a wide range of business analytics use cases – for the purposes of driving revenues, decrease operating costs, and ensure compliancy to regulations.

For each of the use cases covered in this course, the relevant datasets will be described, along with the layman illustration of the challenges and thought processes in creating and deploying the predictive models.

  • Understand the benefits of business analytics
  • Customer loyalty prediction
  • Customer segmentation
  • Product upsell/cross-sell recommendation
  • Supply/demand forecast

Introduction to Data Analytics

  • Types of Analytics
  • Importance of Data Analytics to Enterprises
  • How to Use Analytics Successfully?
  • Best Practices to Initiate Business Analytics Initiatives
  1. Customer Loyalty Prediction
    • Predict customer lifetime and implement preventive strategies to ensure high customer retention.
      Industry: Telco or other services industry
  2. Customer Segmentation
    • Identify groups of customers with similar behaviors to align respective marketing strategies and ultimately improve rates of successful campaigns.
      Industry: Any
  3. Market Basket Analysis
    • Identify upsell/cross-sell opportunities with historical purchase data to generate extra revenue.
      Industry: Retail
  4. Supply/Demand Forecasting
    • Accurately predict supply and demand based on seasonal trends and other context-specific influencing factors for better production planning.
      Industry: Manufacturing or any other supply chain

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