Introduction to Data Analytics for Business
Who Should Attend?
C-LEVEL EXECUTIVES, SENIOR MANAGEMENT PERSONNEL, BUSINESS ANALYSTS, DATA PROFESSIONALS

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
- Customer Loyalty Prediction
- Predict customer lifetime and implement preventive strategies to ensure high customer retention.
Industry: Telco or other services industry
- Predict customer lifetime and implement preventive strategies to ensure high customer retention.
- Customer Segmentation
- Identify groups of customers with similar behaviors to align respective marketing strategies and ultimately improve rates of successful campaigns.
Industry: Any
- Identify groups of customers with similar behaviors to align respective marketing strategies and ultimately improve rates of successful campaigns.
- Market Basket Analysis
- Identify upsell/cross-sell opportunities with historical purchase data to generate extra revenue.
Industry: Retail
- Identify upsell/cross-sell opportunities with historical purchase data to generate extra revenue.
- 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
- Accurately predict supply and demand based on seasonal trends and other context-specific influencing factors for better production planning.
Register Now
Drop us your entry if you are interested to join this course.
You may like
Smart Manufacturing – Improving OEE via Predictive Maintenance and Anomaly Detection
Smart Manufacturing - Improving OEE via Predictive Maintenance and Anomaly DetectionPERSONNELS involve in SMART MANUFACTURINGDuration: 3 DaysTraining Date 20 - 22 July 2020 (KL) 10 - 12 August 2020 (Penang) 19 - 21 October 2020 (KL) 1 - 3 December 2020 (Penang) Class...
Python for Machine Learning and Advanced Analytics
Python for Machine Learning and Advanced AnalyticsIT PROFESSIONALS, DATA ANALYST and PROFESSIONALS with basic knowledge of programmingDuration: 4 DaysThis course will introduce the learner to applied data analytics with Python, focusing more on the techniques and...
Modern Data Engineering In The Cloud
Modern Data Engineering In The CloudPERSONNEL involve in DATA INTEGRATIONDuration: 3 Days, 2 Days (Online Class)Data engineering is the crucial part to enable and operationalize big data analytics and cloud applications in the big data ecosystem. Modern data...