Future Watch, China's Big Data Ecosystem Update

OTSIKKO
ALAOTSIKKO, KUUKAUSI VUOSI
CHINA’S DIGITAL LANDSCAPE AND RISING DISRUPTORS
MODULE 2.9
BIG DATA

AUTHORS
Dr. Edward Tse
Founder and CEO
Team Finland Future Watch Report, December 20172
Mr. Bill Russo
Managing Director and Auto Practice
Lead
Mr. Alan Chan
Associate

BIG DATA AND ANALYTICS
TOPICS
1. WHAT IS BIG DATA?
2. CHINA’S BIG DATA INDUSTRY AND INNOVATORS
3. FUTURE OPPORTUNITIES AND IMPLICATIONS FOR TEAM FINLAND

WHAT IS BIG DATA: THE 5V’S CHARACTERISTICS OF BIG DATA
Source: Literature research, Gao Feng analysis
Big
Data
Volume
Value
Veracity Variety
Velocity
 The massive amount and
growth of data can overtake
traditional storage solutions
 Data is continuously
generated at a
unprecedented speed,
making it harder to
manage and analyze in
real-time
 Traditional data
management fails to handle
different types of
unstructured and structured
data
 Data monetization –
extracting business
insights and revenue
from data
 Trustworthiness of
data in terms of data
consistency,
completeness,
authenticity,
availability and
accountability

DATA WILL CONTINUE TO GROW EXPONENTIALLY
Note: 1 petabyte = 1 million gigabytes; 1 zetabyte = 1 million petabytes
Source: IDC Data Age 2025 Study, Gao Feng analysis
Information Created Worldwide
Zetabytes(ZB)
Key Drivers
 Proliferation of mobile
devices and digital
sensors
 24/7 digital lifestyle
 Advances in computing
power and data storage
capabilities
 Data as a new
competitive advantage
for companies

DATA HAS BECOME ONE OF THE MOST STRATEGIC ASSETS FOR LEADING
TECHNOLOGY COMPANIES
Facebook Google
 Facebook collects 500
terabytes of data daily,
including 2.5 billion pieces of
content, 2.7 billion likes and
300 million photos
 Google processes over 40,000
search queries every second
on average (equivalent to
over 3.5 billion searches per
day worldwide)
Alibaba
2017 Double 11
Shopping Day
 Recorded RMB 168 billion
gross merchandise volume
(GMV)
 Alipay processed 1.5 billion
payment transactions during
the event (up 41% from 2016)
Personalized newsfeed;
Targeted ads
Personalized search results;
Targeted ads
Shopping
recommendations;
Targeted ads

DIFFERENT TYPES OF DATA REPRESENT DIFFERENT LEVELS OF VALUE
CREATION
When
How
What
Who
Where
Breadth of Data
Proprietary response data & transactional data,
and individual consumer triggers such as life event
Known purchase behaviors – tags and shopping history
Likelihood to make a purchase, shopping attitudes, personal
preferences and mode of consumption
Self-reported hobbies, interests and activities
Home ownership, duration of residence, home, value,
purchase amount and date, asset value
Household life-stage segmentation, socio-
economic, and household characteristics
Includes age, income, marital status, children,
education, net worth, occupation, etc.
Contact information, physical & virtual
appearance
Most Predictable
Baseline
Description
Enables Answers to
Key Questions:

BIG DATA HAS ENABLED MANY PERSONALIZED CONSUMER SERVICES
Usage-based Insurance:
Costs are dependent upon
type of vehicle used,
measured against time,
distance, driving behavior
and location
Personalized Newsfeed:
Stream of content based
on the user’s interests,
browsing history,
demographics, and
friends
Targeted Ads:
Ads that are targeted to
specific micro-segments
Micro-segmenting
Consumer/User Data
CASE EXAMPLE

BIG DATA IS ALSO RESHAPING THE INDUSTRIAL SECTOR
Mass customization:
C2B customer-driven small-
patch manufacturing based on
customer personality,
preference and use cases
Predictive Maintenance:
Reduce process flaws, save time and cost
Real-time fraud detection
Digital Plant:
Real-time factory
performance analysis
Real-time factory
rescheduling
Production quality and
yield management
Machine-generated Data
CASE EXAMPLE

THE PUBLIC SECTOR IS ALSO EMBRACING THE BIG DATA OPPORTUNITIES
Public health and transports:
National database of individual’s
health for future healthcare policy
planning
Transportation data for designing
better cities
Public security:
Surveillance cameras
with face recognition
system for public security
purposes
Opening up of tax
data:
Accelerated the
credit investigations of
local banks and their
lending efficiency to
small companies
Government institutions
Policymakers
City Data
CASE EXAMPLE

IN PARTICULAR, BIG DATA HAS BECOME THE BACKBONE OF SMART CITY
ApplicationsAnalyticsData
Connectivity and Sensors
(IoT)
 V2X connectivity
 Embedded modem
 On-board diagnostics
(OBD)/ telematics
 GPS sensors
 In-car cameras
 Temperature/
environmental
sensors
 LIDARS
 Accelerometers
Smart Cities Value Chain
 Location
 Speed
 Origin-destination
 Images
 Videos
 Weather
 Precipitation
 Pollution
 Noise
 Charging data
 Big data
 Data fusion/
amalgamation
 Visualization tools
(e.g. heatmaps)
 Computer vision
 Machine learning
 Artificial intelligence
 Sense-making
 Real-time traffic
conditions
 Congestion prediction
and avoidance
 Automatic incident/
exceptional event
detection
 Parking availability
 Seamless intermodal
public transport
 Dynamic pricing
 On-demand mobility

FUTURE TRENDS IN BIG DATA
Better
Data Analytics
Software
 More non-coder-friendly data analytics tools will be developed, such
as Microsoft and Salesforce
 Demand for real-time streaming insights into data will grow, served by
contemporary tools like Kafka and Spark
 More artificial intelligence technologies will be built-in to data
analytics software to enhance its predicative capabilities
Organizational
Readiness
 Most of the companies will become data businesses
 Chief Data Officer will see a rise in prominence
 Continued shortages of data professionals
From Big Data to
“Fast Data” and
“Actionable Data”
 Fast data - processing of massive data in real time to gain instant
awareness and detect signals of interest on the spot
 Actionable Data - predictive analytics and what-if analysis to prescribe
recommendations to enable businesses to take actions with feedbacks
Others
 Data privacy will become a core issue for business ethics
 Growing threats of biased data for AI applications
 Further opening up of government data

TOPICS
Team Finland Future Watch Report, November 201713

THE CHINESE GOVERNMENT HAS SET AMBITIOUS GOALS IN BIG DATA
INDUSTRY DEVELOPMENT TO FOSTER NEW ECONOMIC DRIVERS
China's 2016-2020 Big Data Industry Development Plan
By the Ministry of Industry and Information Technology (MIIT)
as part of the nation's 13th five-year plan
To increase annual sales of China’s big data industry (including related goods and
services) to RMB 1 trillion by 2020 from an estimated RMB 280 billion in 2015
To target a compound annual growth rate of around 30 percent for the industry's sales
in 2016-2020
To cultivate 10 world-leading big data companies by 2020 and 500 big data application
and service enterprises
To establish 10-15 experimental zones to speed up the industry's development

GUIZHOU IS ONE OF THE PIONEERING PILOT ZONES POSITIONED AS
CHINA’S “BIG DATA VALLEY”
Development of Guiyang as China’s leading
big data hub
Guiyang, the capital of Guizhou Province,
was typically known for poverty
Gui’an New District, a 1,795 sq km suburb
area established in 2014, is the strategic
heart of Guiyang’s technology aspiration
Incentives have attracted companies such
as Foxconn, Microsoft, Huawei, Hyundai
Motor, Tencent, Qualcomm, Alibaba,
Apple, China Mobile, China Unicom and
China Telecom
28 big data scientific research institutions,
and 23 incubators and investment
organizations
 "The big data industry is a perfect opportunity for
Guizhou to develop its economy without
introducing polluting industries, while helping its
poor population shake off poverty. Big data has
also become a magnet for talent, enabling more
young people to settle here"
- Jing Yaping, Deputy director of the provincial
big data development authority

THE CHINESE GOVERNMENT IS DEVELOPING A REVOLUTIONARY SOCIAL
CREDIT SYSTEM TO RATE THE “TRUSTWORTHINESS” OF ITS CITIZENS
Source: Literature research, Wired Magazine, Gao Feng analysis
Plan for a national social credit system
In June 14, 2014, the State Council of
China published an ominous-sounding
document called "Planning Outline for the
Construction of a Social Credit System“
The system is designed to measure and
enhance "trust" nationwide and to build a
culture of "sincerity"
To launch in 2020 and participation is
mandatory
Two leading “experiments”
- China Rapid Finance, partnering with
Tencent WeChat (850 million active users)
- Seasame Credit, run by Ant Financial
Services Group (affiliate of Alibaba)
Rewards and "special privileges" are given to those
citizens who prove themselves to be "trustworthy"
on Sesame Credit, for example:
- Rent a car without leaving a deposit
- Faster check-in at hotels
- Use of the VIP check-in at Beijing Capital
International Airport
- Apply for Singapore travel without
supporting documents such as an employee
letter
- Fast-tracked application to a coveted pan-
European Schengen visa

SESAME CREDIT COLLECTS A HOLISTIC RANGE OF DEMOGRAPHIC,
BEHAVIORAL AND TRANSACTIONAL DATA FROM ALIPAY USERS
Source: Literature research, Wired Magazine, Gao Feng analysis
 Individuals on Sesame
Credit are measured by a
score based on five
categories
Credit History
 Does the citizen pay their electricity or
phone bill on time?
Fulfilment
Capacity
 What is the user's ability to fulfil his/her
contract obligations?
Personal
Characteristics
 Verifying personal information such as
someone's mobile phone number and
address
Behavior and
Preference
 What is the user’s shopping habit? What
types of products does the user buy?
Interpersonal
Relationships
 What does their choice of online friends
and their interactions say about the
person being assessed?
CASE EXAMPLE

TOUTIAO IS A DISRUPTIVE NEWS PLATFORM PROVIDING HIGHLY
PERSONALIZED CONTENT
Source: Toutiao, Financial Times, Literature research, Gao Feng analysis
CASE EXAMPLE
Augmented Reality (AR)Competitive advantages in
content generation, distribution and monetization
Toutiao’s exponential growth
Basic facts:
By analyzing the features of content, users and users’
interaction with content, Toutiao’s AI-powered algorithm
models generate a tailored feed list of content for each
individual user
Now valued at USD 20Bn (from USD 500M in 2014)
Launched in August 2012 based in Beijing
Founder: Zhang Yiming
100M daily active users in 2017Q1
Average daily usage time: 76 min
Hired Ma Wei-Ying, former assistant managing director of
Microsoft Research Asia, to lead its AI Lab
 User-generated and professional-generated
content in various media forms: text, short
videos, Q&As
 Provide incubator and media lab services for
curated content makers
 AI-generated content live feed
 Understand user’s emotions and behavioral
characteristics through machine learning,
analyze and predict user’s profile
 Personalized news content – “Thousand
people, thousand interfaces”
 Technology barrier: Leverage big data to
accumulate user understanding overtime
46
11
335
107
507
141
2016H22015H2
Total length of read (Billion mins)
Total no. of read (Billion)
No. of articles (Million)
Content
Generation
Content
Distribution
Content
Monetization
 Business model: Targeted ads, re-direct traffic
to E-commerce sites
 Earned USD 869M in 2016 from in-app ads
with the goal to reach USD 10Bn by 2020

DAYIMA IS A LEADING FEMALE HEALTH MANAGEMENT MOBILE APP
LEVERAGING DATA-DRIVEN INSIGHTS FOR CROSS-SELLING
CASE EXAMPLE
Company Overview User Big Data Analytics
 Launched in 2012, most popular female
health management app in China
 Basic functions: recording and
predicting periods
 Also offers customized services, E-
commerce platform and online
communities
 Raised Series E funding in 2015 with 130
Million RMB
Properties and Tags Pyramid (PTP) system
Who is she?
Properties Behavior Tags
24 Years
Old
Beijing
Period Cycle 34 Days
Preparing for Pregnancy
Read post:
Dysmenorrhea Syndrome
Purchased:
Black Sugar Tea
Search: Dysmenorrhea
Data Collection and Cleaning
Big Data Analytics
CustomizedProductRecommendation
Dayima

ZHOUHEIYA, A SPECIALIZED FAST FOOD CHAIN, SPOTTED A NEW
PRODUCT OPPORTUNITY BY LEVERAGING BIG DATA INSIGHTS
CASE EXAMPLE
 By using Alibaba’s big data analytics service,
Zhouheiya discovered that the keyword “crayfish”
is searched most during April to August and its
sales peak is between May and June
 Zhouheiya found out that the target customer
portfolio of crayfish highly overlap with their
existing one
 Consumption of crayfish usually do not
cannibalize the demand of other snacks
 Historically, braised duck are sold least in spring
and July. The gap could potentially be filled by
launching new crayfish products
Sold 20,000 units of crayfish within 10 days
with a unit price of 69.9 RMB
 A Chinese fast-food chain famous for its spicy
braised duck
 Expanded the product line to crayfish in May
2017
Zhouheiya ( 周黑鸭 )
Market insights through big data analytics

TOPICS
Team Finland Future Watch Report, November 201721

FINLAND HAS LEADING ADVANTAGES IN ENERGY, CLIMATE AND TAX TO
BECOME THE WORLD’S POWERHOUSE OF DATA CENTER
Source: Invest in Finland, Copenhagen Economics Report: Finland’s economic opportunities from data center investments, Gao Feng analysis
Finland’s leading advantages:
Cold weather to chill servers and keep costs down
(Invest in Finland indicates that it is easy to save up
to 50% on energy costs in Finland compared to other
European locations)
Over 180,000 lakes in Finland - plenty of water
available for renewable energy and cooling needs
Spacious country with many potential sites for data
center investments (Invest in Finland has identified
36 investment-ready locations )
Electricity tax for data centers was reduced to the
same level as industrial electricity tax - the most
competitive in northern Europe
Strategic location between Asia and Europe
Ultra-fast submarine cable
World’s leading tech companies with
data centers set up in Finland
According to a Copenhagen Economics report, Finland’s data center industry has the potential to support
as many as 32,900 jobs and contribute EURO 2.3 billion a year to the national output by 2025 (3x from now)
Google’s advanced data center in Hamina

THERE ARE ALSO LEADING BIG DATA SOLUTIONS PROVIDERS IN
FINLAND
 BIGDATAPUMP is a leading analytics company
specialized in big data and cloud transformation
 Founded in 2012 based in Turku; by ex-Nokia
experts in Microsoft Azure and cloud analytics
 Over 100 customer cases in Europe, North
America, Asia and Middle East
 Turnover in 2016: EURO 3.4M
 Acquired by Affecto (a leading company for data
and business intelligence solutions in Finland) in
Dec 2016
 Core competencies: Advanced analytics, data
visualization and exploitation of big data
 Services: Customer analytics, profitability
management, and IoT solutions
 Founded in 2009 based in Helsinki
CASE EXAMPLE

ALIBABA HAS RECENTLY SET UP A JOINT INNOVATION CENTER IN
FINLAND TO PROMOTE LOCAL BIG DATA DEVELOPMENT
CASE EXAMPLE
 Alibaba Cloud, a cloud computing company
affiliated to Alibaba Group, and Eficode Oy, a
leading Finnish digital company based in
Finland, jointly opened an innovation center
in Helsinki in Dec 2017
 Alibaba and Eficode formed strategic
partnership in Nov 2017 to bring a
comprehensive range of Alibaba Cloud
offerings to Northern Europe and Nordic
companies in the Chinese market
 Goals:
- To provide a platform to enhance the
collaboration between Nordic and Chinese
businesses, researchers and education
institutes
- To provide R&D resources and workspace
to the local big data sector and related
businesses
- To develop solutions that will help
enterprises address the digital challenges
in business expansion and digital
transformation

POTENTIAL SINO-FINNISH OPPORTUNITIES ON BIG DATA
To attract Chinese tech players to
set up data centers in Finland
From China to Finland
Value propositions for Chinese tech companies
Finland’s technical know-how in data centers
Finland’s talent pool of data professionals
Finland as a strategic platform supporting the
internationalization of Chinese tech companies
Value propositions for Finland
Cross-border investments
Job creation
Strengthen Finland’s reputation as the world’s
epicenter for data center
From Finland to China
Value propositions for Finland
To establish Finland’s global technology
leadership in big data industry
To form Sino-Finnish cooperation projects and
build government connections
Value propositions for China
To benefit from Finland’s best big data
technologies and talents
To accelerate the development of China’s big data
industry
Finland’s leading big data companies to
establish presence in China’s big data hubs
Remarks:
Finnish companies can purchase data from data service providers in China for market
intelligence purposes – but China’s cybersecurity law requires foreign technology firms to store
certain “important business data” locally, including personal data

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