PwC's Data-lympics 2019

Human and machine

28-29 January 2019

Event details

Date: 28-29 January 2019

Time: 9:00 - 18:00

Venue: PwC Training Centre, 19/F, Tower A, Manulife Financial Centre, 223-231 Wai Yip Street, Kwun Tong, Kowloon

Judging panel: PwC Hong Kong Risk Assurance Data & Analytics team

What is Data-lympics?

Data-lympics is a competition event for people like you who are interested in Data Science to explore, collaborate, discover and share insights/ideas/experiences about large, rich, and complex datasets. Apart from the competition itself, there will be other supporting activities ranging from educational workshops to networking opportunities with peers and industry professionals. 

Why Data-lympics?

We would like to: 

  • Promote a culture of innovation: Data-lympics help inspire a data-driven culture by engaging participants through team collaboration and innovative thinking. By 2020, almost all roles will require some type of data and analytics skills. Data-lympics encourage students to have fun and gain a hands-on introduction to analytics.
  • Identify and groom talents: Data-lympics uncover innovative and creative thinkers and PwC is happy to groom students to expand the talent pool in Hong Kong.
  • Advocate the adoption of machine learning: Data-lympics can demonstrate that data and analytics solutions are easily accessible by any organisation, even those with little business intelligence and analytics experience. Data-lympics can also quickly show how the application can help drive business value.

University students (including both undergraduate and post-graduate)

Registration deadline: 4 January 2019

Please register through your respective university representatives by providing the following:

  • Name of the team
  • Names and contact details of team members
  • Name of team leader


For other institutions or any enquiry, please contact:
Chris Mo, Senior Manager, Data & Analytics, Risk Assurance, PwC Hong Kong


City University of Hong Kong 

Department of Economics and Finance
Dr. Junchao Xiao -

Hong Kong Baptist University
Joseph Ng -

Hong Kong University of Science and Technology
School of Engineering
Vince Chow -

The Chinese University of Hong Kong

Wing Cheong Lau -

The Hong Kong Polytechnic University

Chris Mo -

The Open University of Hong Kong

Dr. Raymond So Wing Cheung -

The University of Hong Kong

Dr. Eric Li -

Faculty of Business and Economics
Laraine Ko -


  1. PwC’s Data-lympics is a 2-day event that allows participants from universities to have an opportunity to demonstrate how data & analytics is used to address business challenges. It will start in the morning of 28 January 2019 and end with the final presentation of 10 teams scheduled to take place on 29 January 2019.
  2. The final presentation duration will be 10 minutes plus 5 minutes question and answer.
  3. In addition to the given datasets, teams are free to use any open data or crawl data from the Internet.
  4. A team must consist of at least 2 and at most 4 participants. Participants MUST be university students (including both undergraduate and post-graduate). Participants MUST register and show up physically on Day 1 morning. 
  5. Each team will work on only one topic selected from the list. For this competition, teams can't propose their own topics.
  6. All teams must begin coding at the same time. All development work must be done within the development period stated in the event schedule.
  7. Collaboration amongst teams is not allowed.
  8. PwC will own the rights to projects from top 3 winners (i.e. source codes and other deliverables) created during the Data-lympics. Other participants will own the rights to their projects they create during the  Data-lympics. The copyright, intellectual property and other rights of all datasets as provided in the  Data-lympics are solely owned by PwC. Participants are required to sign a non-disclosure agreement for the data provided during the  Data-lympics competition.
  9. The Organising Committee reserves the right to disqualify participants who are late, absent, or show-up with improper behaviour during the Data-lympics.
  10. During the event, participants are responsible for their own personal belongings; the Organiser will not take responsibilities for any lost property.


Evaluation criteria:

Relevance - 30 Points
Is the solution relevant to the business issue?
Is the solution relevant to Hong Kong/China?

Impact - 10 Points
Is the solution adding value to the business?

Innovation - 20 Points
Does the solution introduce new ideas or methods?
Does it make use of open data?

Technical achievement - 30 Points
Readiness to use
Ease of use

Communication and presentation - 10 Points

Day 1:  28 January 2019 (Monday)
9:00 Registration
9:30 Welcome speech
10:00 Competition briefing
11:00 Competition
18:00 End of Day 1; Venue closed
Day 2: 29 January 2019 (Tuesday)
9:00 Registration
9:30 Competition
12:00 Solution submission
15:00 Announcement of shortlisted teams
16:00 Presentation
17:45 Award announcement
17:50 Closing speech from Jennifer Ho, PwC’s Global Risk Assurance Data & Analytics Leader
18:00 End of event

The top 3 winning teams will be awarded with two-months internship or one-year placement programme*, plus:

- Champion: HK$20,000 cash

- 1st runner up: HK$12,000 cash

- 2nd runner up: HK$5,000 cash

* With PwC Hong Kong and Mainland China's Risk Assurance's Data & Analytics team. For internship and graduate programme details, please visit:

Q: Who can attend?

A: Any undergraduate or post-graduate students above age 18 can attend our Data-lympics. No experience with data science is assumed.


Q: Any restriction on which university student can participle?

A: Absolutely NOT! We welcome students from anywhere.


Q: What should I bring?

A: You should bring your own laptops, chargers and any related softwares.


Q: How much is this going to cost?

A: Data-lympics is 100% free. We will be providing free food and drinks!


Q: Other questions?

A: If you have any more questions or concerns feel free to contact Chris Mo, Senior Manager, Data & Analytics - Risk Assurance at You can also check out our Facebook page.