Presentation to HKUST MBA class

1. Big Data:
Getting Smarter
Charles Mok
Legislative Councillor (Information Technology)
2016.4.30 @ HKUST MBA course sharing

3. Datasets
getting
bigger

4. Big Data
ecosystem
is maturing
Big Data startups
received $6.64B in
venture capital
investment in 2015,
11% of total tech VC.

6. Convergence of cloud,
analytics, mobile and
social technologies

7. Are these your questions?
1. How can it help enterprise stay competitive?
2. How to drive innovation, growth & transformation?
3. How to integrate big data into operations and business
development while keeping costs low?

8. How can big data help meet business goals?
Reduce
cost
Improve
productivity
Customer
acquisition
and
expansion
8
Next-gen sales and
operations planning
Improved
segmentations to
up-sell and cross-sell
Process and
information
automation

9. Is big data
still THE thing
in 2016?
Plateau reached?
New hype?
AI,
machine intelligence,
deep learning…
Enterprise tech:
Legacy infrastructure
makes deployment
complicated

10. Now that I have data, what insights am I going to extract from it?

11. Data: The More
the Better?
Size is no longer king
content and
context more
important
time, location, associations,
links, interdependencies, etc.

12. Problem arises
structured data (your company's
proprietary information) x
unstructured data (public
sources such as social media
streams and government feeds)
= ?????
Data cleansing, labeling
and organising become
essential before the data
is made USEFUL
 New opportunities /
business?

13. Example:
Big Data for Financial Modelling
Boutique firm specialises in providing
non-traditional / alternative data
From social media buzz to satellite
images, mined by cutting-edge computer
scientists
Allows new insights for investors and
analysts, users can develop their own
valuation model

14. Help analyze massive
amounts of data and derive
predictive insights…
and help data scientists to do a
quicker and better job.
The rise of algorithm & AI to
handle unstructured data for
business intelligence

15. Example: FinTech

16. The flow
Aggregate
Anonymize
Analyze
Data from business
operations
Media
Customer
engagement
16
Actionable
Data

17. Experiment  Deployment
Processes
Discoveries
Decisions
Applications

18. •More precise decision-making
•Real time analysis and capture opportunities
•Value-adding and knowledge management
18

19. Emerging trends
in big data

20. IoT, Cloud and
Big Data
come together for real
time analytics
consumer can use

21. Chatbots are taking over: Big tech companies’ new battling ground
DigitalGenius:
 chatbot startup raised US$4.1 million funding early April
2016
 harness the technology for automating customer service
operations.
Requires combing through lots of data
and returning an answer by machine learning

22. New government initiatives
Increase the Wi-Fi
hotspots to over
30,000 in Hong
Kong.

23. Big Data x Open Data:
Transport as case study
23

24. No Open Data, No Smart City
What can developers use at present?
Available for free - items in transport:
● Journey time indicators
● Speed map panels
● Traffic snapshot images
● Traffic speed map
● Routes and fares of public transport
● MTR routes, fares and barrier-free facilities
● Electric vehicle charging station locations

25. Upgrade of TIS in the
next few years to
support real time data,
analytics, and…
Open data?

26. Overseas: government support to sharing real time data/API

27. What difference does it make? In HK we have an approximate

28. In Tokyo and London, we get real time info

29. Policy perspective: Big data / Open data
Access to informationTransparency
Participation
A better citizen experience
for a more connected
citizenry

30. Big Data and Citizen
Engagement
• Public participation
system
• Smart Engagement:
Polling and data mining
• Identify public opinions
for targeted policy
initiatives

31. Use of personal-identifiable data
- growing concern for consumers
- focus for regulators
- battleground for consumer trust
31
Companies need to proactively respect
and protect consumer data

32. Thank You
charlesmok@charlesmok.hk
Facebook: Charles Mok 莫乃光
www.charlesmok.hk