Business Data Analytics Program (Instructor-Led Live Class)

  • Course level: Intermediate


Data-Driven Decision for Improvements and Performance

Business Analytics Introduction

  • A high-level introduction of business analytics

Types of Analytics

  • Descriptive analytics
  • Predictive Analytics
  • Prescriptive Analytics 
  • Descriptive, Predictive, and Prescriptive Analytics Techniques
  • Big Data Analytics
  • Web and Social Media Analytics 
  • Machine Learning Algorithms

Analytics life cycle

  • About building a center of analytics excellence:
  • Top Management Support
  • Analytics Talent
  • Information Technology (IT)
  • Innovation

Data Visualization

  • Why a picture is better than a thousand words
  • Common Data Visualization Tools
  • Interpretation of some common data representation chart

Business Survival with Analytics

  • Measures, Metric, KPIs
  • The Cashflow Gap
  • Managing Volatility & Uncertainty of Variability  

Use cases : 

Customer Churn Prediction 

Customer churn is what happens in every service sector with multiple firms offering the same service to consumers at a different price point or discount in some cases, inundated by offers they may choose to leave partially or fully. This use case will work through how to predict churn before it happens, identify why and isolate customers who would likely churn by introducing offers to make them stay with the current service provider. 

To do this we will be leveraging low code tools (KNIME,  ORANGE) and presenting a dashboard of our findings in PowerBI.

Demand  Prediction (Bike rental service)

Demand Prediction is the norm in all service industries, knowing how much to produce, buy or order can make an organization profitable, in this case, a study we look at a bike-sharing service and work at predicting how many bikes should be placed in a certain location for rent. 

Start Date: March 5, 2022

Class Schedule
Every Saturday and Sunday, 2 pm AST

Topics for this course

6 Lessons

Module 1?

Introduction to Data Analytics
Introduction to Data Analytics2:33:50

Module 2

Module 3

Module 4?


Module 5

Module 6

Practical Data Analytics Course