Back to School of Management  Back to Executive Programme 


Executive Certificate in Big Data & Analytics for Business

big data  
Download brochure                                                                                                                            
Apply NOW  



Programme Objectives

Upon completion of the Programme, students should be able to:

1. Understand the overall process of data analytics in solving business problems
2. Develop a big data strategy and understand how to build a data science team
3. Apply practical techniques to collect data from social media, websites and open data source platforms
4. Apply simple coding to standardize data stored in different formats and different files more effectively 
5. Understand and describe popular big data analytics models in business prediction and its applications
6. Use data visualization tools to generate simple dashboard reports for analysis 
​7. How to evaluate the predictive power and accuracy of your data analytic model

Course Contents

The programme consists of two modules. There is a total of 45 hours of lectures including a group presentation.
Module 1: Understanding Big Data, How It Applies to the Business World and Data Preparation
Module 2: Introducing Fundamentals of Big Data Analysis Models and Result Measurement of Big Data Projects

Module 1: Understanding Big Data, How It Applies to the Business World and Data Preparation
Unit 1: Understanding of Big Data
- What is Big Data and why Big Data
- 3 types of data
- Characteristics of Big Data (6Vs): Volume, Velocity, Variety, Veracity, Valence, Value
- How does Big Data apply to the business world
- What are and what are not Big Data problems
- How to build a Big Data strategy
- How to define a correct Big Data question
- How to build a Data Science Team
- Data privacy issues
Case Studies: Airbnb, Allstate Insurance

Unit 2: How to prepare data from different sources
- Collect data from online channels: social media, websites, Google Form and Google Analytics
- Collect data from open data sources: DataOne, the Data Studio at Hong Kong Science Park
Case Studies: New York Times
Hands-on Experience*: Introduction to Python and run basic Python code to capture data from Facebook

Unit 3: The importance and practical technique of data cleansing
- How to enrich and transform your data set 
- How to deal with your huge database in Excel spreadsheets
- How to consolidate multiple spreadsheets
- How to standardize different input pattern of the same data field
- How to link-up different data of the same customers from different Excel spreadsheets
Hands-on Experience*: 
- Introduction to R language and run basic R codes to standardize data into different formats
- Introduction to relational database concept and run simple SQL statements to link-up data from different Excel spreadsheets

Module 2: Introducing Fundamentals of Big Data Analysis Models and Result Measurement of Big Data Projects
Unit 4: The fundamentals of Big Data prediction models
- How to set an objective for data analysis
- What is a prediction model?
- Differences between business intelligence and Big Data analytics
- Overview of Big Data prediction models
- 3 most popular Big Data prediction models applying on marketing:
   i) Customer Segmentation
  ii) Up-selling and Cross-selling
 iii) Customer Retention

Case Studies: Bank, e-Commerce, Retail and Telecommunications Industry

Unit 5: How to visualize your data and find out insights
- What is data visualization?
- Presentation of Big Data in graphical format for grasping difficult concepts or identifying patterns 
- How to organize marketing dashboards with interactive charts
- Explore info-graphics creation for marketing story-telling
Hands-on Experience*:
- Use popular data visualization tool Tableau to generate real data reports
- Design an interactive graph with a freeware Plotly and Excel

Unit 6: How to measure the success of a Big Data analytics project 
- How to turn the insights from business analysis into action
- How to evaluate the predictive power and accuracy of your models
- How to measure the success of data analytics/ KPI setting
Case Studies: Logistics Industry, Telecommunications Industry, Digital Advertising Industry

Unit 7: Group presentations, guest speakers & award presentation
Group Project: Understand how Big Data applications can have a good impact to society problems
Visit to the Data Studio at Hong Kong Science Park

* Although no prior programming knowledge is required, students are expected to be guided in "learning by doing" to perform some simple programming tasks in order to strengthen their foundation and mindset on Big Data applications. 


Target Participants

Senior and middle-level IT professionals, digital marketing, customer relationship management, sales, e-Commerce, business leaders, heads of department, entrepreneurs, etc. Other participants who are keen to leverage data to make smarter and quicker decisions are welcome to join the course.

Entry Requirements

1. A recognized degree in any discipline; or
2. A recognized Associate Degree / a Higher Diploma or equivalent, and at least 2 years of work experience; or 
3. Professional qualifications
Applicants with other qualifications and substantial senior level work experience will be considered on individual merits.


The programme will be assessed by one group presentation.


An "Executive Certificate in Big Data & Analytics for Business" will be awarded to students who attend 70% of the class and pass the group presentation.

Medium of Instruction

Cantonese, supplemented with course materials in English.


    Download brochure Apply NOW   ***FULL***                                       


Programme Enquiry

Tel: 3762 6188