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Accounting & Finance Finance and Compliance

Certificate for Module (Big Data Governance and Data Compliance)
證書(單元 : 大數據治理及數據合規)

CEF Reimbursable Course

CEF Reimbursable Course

Course Code
Application Code

Study mode
Start Date
14 Apr 2024 (Sun)
Next intake(s)
Jun 2024
2 months to 3 months
Course Fee
Course Fee: $8600 per programme (* course fees are subject to change without prior notice)
Deadline on 29 Mar 2024 (Fri)
2867 8331
2861 0278
Apply Now

Today and Upcoming Events

Accept new applications for Apr 2024 intake! There will be practical classes in the computer laboratory. The programme covers big data processing lifecycle, business challenges as well as big data opportunities in business and finance. Also, our seasoned lecturer discussed various managerial issues related to big data governance as well as data security and compliance. Welcome to your online application!


The programme aims to provide students with the key concepts of big data and related operational and ethical issues. It will discuss big data opportunities and challenges, fraud detection, data protection, ethical and compliance issues from managerial perspectives globally. Besides, best practices for data security and compliance, regulatory requirements will be covered in the programme.

Big Data

Programme Details

On completion of the programme, students should be able to
  -describe big data concepts and related ethical issues of data collection and handling;
  -identify opportunities and threats using big data;
  -explain how various technological elements enhance governance and compliance;
  -analyze potential risks and challenges in handling fraud detection and prevention; and
  -discuss the standards and best practices of data security and compliance.

Application Code 2180-FN055A Apply Online Now
Apply Online Now

Days / Time
  • Saturday, 1:00pm - 7:00pm
  • 30 hours per programme
  • Hong Kong Island Campus
  • Kowloon East Campus


Course Content :

(1) Introduction to Big Data

  • Overview of big data, data science and analytics
  • Introduction to computing and communication technology for big data: cloud computing, mobile computing and 5G
  • McKinsey big data processing lifecycle: data discovery, data aggregation, planning of the data models, data model execution, communication of the results, and operationalization.
  • Ethical issues of data collection and handling

(2) Big Data Governance and Business Implications

  • Overview of big data technology and FinTech: Chatbot, Robo-advisor, Algo-trading, Insurtech, Wealthtech, Regtech, PropTech
  • Business and technological implications of big data: User Interface (UI) and User Experience (UX) as a result of Open Application Programming Interface (API) policy in HK and the rest of the world
  • Business challenges and big data opportunities in business and finance
    • Asset management
    • Customer analytics
    • Virtual banking
    • Financing and funding
    • Wealth management
    • Credit analysis
    • Risk management
    • Fraud detection
  • Contemporary issues of big data governance from managerial perspectives
    • Governance lifecycle and critical components
    • Tools, structures and policies executions vs human adoptions
    • Big data talents and expertise developments
    • Corporate social responsibility (CSR) and sustainability of best big data governance practices
    • International big data governance principles, models, guidelines and regulatory trends
    • Minority report vs potential discriminations and abusive use of data powers
    • Critical analysis on how far Artificial Intelligence (AI) automation should go in decision making
    • Mindfulness and ethical applications on big data in big data modelling as well as in Deep Learning (DL)

(3) Data Security and Compliance

  • Overview of legal and regulatory framework related to data protection and compliance
    • General Data Protection Regulation (GDPR) and related compliance
    • Personal Data (Privacy) Ordinance (Cap. 486)
    • Six Data Protection Principles in Data Privacy Law
    • California Consumer Privacy Act (CCPA)
  • Security risks for big data and infrastructures
  • Ethical usage of consumer data for value creation as in the data value chain
  • Issues related to compliance and regulatory reporting
  • Fraud detection and data security
    • Hacking activities, corresponding categories, symptoms and measures
    • Vulnerable loopholes
    • Fraud detection techniques with predictive analytics: Machine Learning (ML) vs Deep Learning (DL)
    • Best practices for implementing big data for fraud prevention
    • How big data analytics enhances monitoring performance and quicker decisions in detecting suspicious behaviour, uncovering threats and vulnerabilities, preventing security incidents, and backing up forensic analyses
    • Risk prediction as in risk management
    • Potential for discrimination
    • Privacy framework with appropriate approach to notice and consent
    • Ethical and fair usage of big data to achieve value-based innovation
    • Compliance and regulatory reporting
    • Corporate fraud detection and prevention
    • Big data risk management and governance cycle
    • Best practices for data security and rapid recoveries
    • Issues of open Application Programming Interface (API) and Internet of Things (IoT)
Assessment method: One 30-minute quiz + One assignment + Group Project

Upon successful completion of the programme, students who have pass the continuous assessment and final assessment with attendance no less than 70% will be awarded within the HKU system through HKU SPACE a Certificate for Module (Big Data Governance and Data Compliance).



(1) Prof Stephen Ng
Prof. Ng is a seasoned executive for InnoTech ICT and Digital business. He launched many first innotechs in the region, namely the first Broadband, 3G, 4G, e-commerce, m-commerce,  Mobile Apps, SaaS cloud, Biometric IDaaS, AI automation, Social Analytics through Machine Learning etc., Graduates of FinTech, AI, and Education from various Universities including Oxford and Bristol. He has obtained professional qualifications including Finance, IT, Security, Psychology, Education, Legal Studies and Management.
Professor Ng has taught the existing programme at HKU SPACE with topics related to Big Data, Governance & Compliance over three years as well as delivered the various seminars related to Big Data, AI and FinTech.
He has served as Company Doctor and Mentor for Corporates and Startups over years, successfully helping Intellectuals Transfer and Wisdom Inspirations on different dimensions across industries and governments in the region as well as sharing and inspiring Executives at various levels from his rich insights and experiences.
Professor Ng was also invited as Honouray Advisor for various international NGOs, forums, academics and professional settings. He has proactively promoted Mindfulness-Based Entreprenuarship & Intelligence Transformations in Public and Private sectors, and proposed the Happiness Value-Chain approach in Business Transformation and Benchmarking on international leadership forums.
He has received various awards from government and renowned communities from Tech Gibs to Life Hackings, included NASA, TechCrunch & HKSAR government etc. Currently, he is conducting R&D projects in Blockchain 4.0, RegTech 2.0 designs and various startup projects. He continues serving the MindTech disruptions towards better Humanity and Technological Advancements.

(2) Mr Thomas Lee
Mr Lee is a computer and project management professional who has worked in the information technology and data science industry for over 30 years under vendor environments including HP Inc., Dell, Fossil, Motorola network and GP Batteries. In the past ten years, Mr Lee focused on new product introduction, design for manufacturability, quality assurance & production risk management among manufacturing plants in China & Taiwan utilizing various data sciences tools and methodologies.  Mr Lee is qualified as a Microsoft Certified Trainer in delivering Microsoft training modules based on Azure technology.  He has been teaching courses related to Big Data, Cloud Computing, Machine Learning, Cyber Security and Fintech since 2020.  Mr Lee is a certified Project Management Professional, PMP from Project Management Institute PMI, US from 1998 and a Certified Scrum Master since 2018. Mr Lee holds a Master of Health Science degree in Biomedical Engineering from University of Toronto, St. George Campus, Canada.  He currently works on projects as an enabler for Inclusion and Accessibility utilizing the artificial intelligence technology. 

Guest Speaker

Mr Barry Chin
Mr Chin is a Registered Professional Engineering in Hong Kong Canada, a Chartered Electrical and Mechanical Engineer in the United Kingdom, as well as a Solicitor of Hong Kong. He obtained his Engineering degree in Canada, majoring in electrical and mechanical engineering. He has also worked in various countries including Hong Kong, United Kingdom, Italy, Germany, Canada and United States of American specializing in all aspect of MechaTronic fields. In particular, Mr Chin had worked for Canadian Marconi Company, a company in the business of designing military equipment and weapon. There, for the company, Mr. Chin was responsible for designing radar technology. Finally, Mr Chin worked as a consultant for Digital Equipment Corporation, amanufacturing company of mainframe commercial computers.
In early 1990’s, Mr Chin decided to pursue further studies in the legal field and he completed his LL.B.(Hons) degree in 1996. He began practicing as a Solicitor in 1998 and his efforts have earned him remarkable achievements. For example, he now serves as the Vice-President of The Forensic CPA Society of Hong Kong and The Association of Hong Kong Professionals. He has also served in various committees of the Hong Kong Government for a number of years, namely the HKIRC Consultative and Advisory Panel, the Panel of Adjudicators of the Obscene Articles Tribunal, the Office of the Government Chief Information Officer and the Health Level Seven International. Finally, he is also an Honorary Legal Advisor of the International Police Association Hong Kong (SAR) Section.

Class Details


Apr 2024 intake

Lecture Date Time
1 14 Apr 24 (Sun) 13:00 - 19:00
2 21 Apr 24 (Sun) 13:00 - 19:00
3 27 Apr 24 (Sat) 13:00 - 19:00
4 4 May 24 (Sat) 13:00 - 19:00
5 11 May 24 (Sat) 13:00 - 19:00

Remarks: Tentative timetable is subject to change, and course commencement is subject to sufficient enrollment numbers.


Application Fee

HK$150 (Non-refundable)

Course Fee
  • Course Fee: $8600 per programme (* course fees are subject to change without prior notice)

Entry Requirements

Applicants should hold an Advanced Diploma, a Higher Diploma or an Associate Degree awarded by a recognized institution. Applicants with other equivalent qualifications will be considered on individual merit.

**Please upload copy of HKID and proof of degree while applying online. 


  • The CEF Institution Code of HKU SPACE is 100
CEF Courses
Certificate for Module (Big Data Governance and Data Compliance)
證書(單元: 大數據治理及數據合規)
COURSE CODE 33C131595 FEES $8,600 ENQUIRY 2867-8331
Continuing Education Fund Continuing Education Fund
This course has been included in the list of reimbursable courses under the Continuing Education Fund.

Certificate for Module (Big Data Governance and Data Compliance)

  • This course is recognised under the Qualifications Framework (QF Level [5])


Online Application Apply Now

Application Form Download Application Form

Enrolment Method
Payment Method
1. Cash, EPS, WeChat Pay Or Alipay

Course fees can be paid by cash, EPS, WeChat Pay or Alipay at any HKU SPACE Enrolment Centres.

2. Cheque Or Bank draft

Course fees can also be paid by crossed cheque or bank draft made payable to “HKU SPACE”. Please specify the programme title(s) for application and the applicant’s name.. You may either:

  • bring the completed form(s), together with the appropriate course or application fees in the form of a cheque, and any required supporting documents to any of the HKU SPACE enrolment centres;
  • or mail the above documents to any of the HKU SPACE Enrolment Centres, specifying  “Course Application” on the envelope.  HKU SPACE will not be responsible for any loss of payment sent by mail.
3. VISA/Mastercard

Applicants may also pay the course fee by VISA or Mastercard, including the “HKU SPACE Mastercard”, at any HKU SPACE enrolment centres. Holders of the HKU SPACE Mastercard can enjoy a 10-month interest-free instalment period for courses with a tuition fee worth a minimum of HK$2,000; however, the course applicant must also be the cardholder himself/herself. For enquiries, please contact our staff at any enrolment centres.

4. Online Payment

Online application / enrolment is offered for most open admission courses (course enrolled on first come, first served basis) and selected award-bearing programmes. Application fees and course fees of these programmes/courses can be settled by using "PPS by Internet" (not available via mobile phones), VISA or Mastercard. In addition to the aforesaid online payment channels, continuing students of award-bearing programmes, if their programmes offer online service, may also pay their course fees by Online WeChat Pay, Online Alipay and Faster Payment System (FPS). Please refer to Enrolment Methods - Online Enrolment  for details.


  • If the programme/course is starting within five working days, application by post is not recommended to avoid any delays. Applicants are advised to enrol in person at HKU SPACE Enrolement Centres and avoid making cheque payment under this circustance.
  • Fees paid are not refundable except under very exceptional circumstances (e.g. course cancellation due to insufficient enrolment), subject to the School’s discretion. In exceptional cases where a refund is approved, fees paid by cash, EPS, WeChat Pay, Alipay, cheque or PPS (for online payment only) will normally be reimbursed by a cheque, and fees paid by credit card will normally be reimbursed to the payment cardholder's credit card account.
  • In addition to the published fees, there may be additional costs associated with individual programmes. Please refer to the relevant course brochures or direct any enquiries to the relevant programme team for details.
  • Fees and places on courses cannot be transferrable from one applicant to another. Once accepted onto a course, the student may not change to another course without approval from HKU SPACE. A processing fee of HK$120 will be levied on each approved transfer.
  • Receipts will be issued for fees paid but HKU SPACE will not be repsonsible for any loss of receipt sent by mail.
  • For payment certification, please submit a completed form, a sufficiently stamped and self-addressed envelope, and a crossed cheque for HK$30 per copy made payable to "HKU SPACE" to any of our enrolment centres.