This talk is slightly modified from previous talks I offered that were teasers or aimed for students. In this talk I again provide an overview of big data terms, technologies, and the heroes and villains. But half this talk covered Asia and Hong Kong big data opportunities.
For more information please go to http://infoincog.com.
8. components: creating value from data
servers
traditional
dbms
visualization
storage
columnar dbs
network
s
hardware
software
nosql
platforms
hadoop
appliances
people
traditional
IT
platform
architects
comp.
scientists
data
scientists
17. example: moving to hong kong
adapted from gartner hype cycle
convenient, good
business atmosphere,
good people
visibility/expectations
limitless
pubs!
better network,
good schedule
new job in
hong kong
trigger
nobody knows
how to walk on
sidewalks!
time
inflated
disillusionment
productivity
expectations
enlightenment
18. what was the trigger?
•
•
•
•
unbounded compute
cheap storage
data accessibility and world datafication
internet scale: yahoo! and google
– offspring of hadoop
19. big data: where are we
today?
adapted from gartner hype cycle
visibility/expectations
this will be caused by
a lack of data science
time
trigger
inflated
disillusionment
productivity
expectations
enlightenment
28. how does your business start?
management
commitment
data-driven decision
making
technologists (data scientists)
meeting with other
companies’ leadership
will firm up commitment
a presentation to
management may help
them believe
can hire or contract
here in HK
technologies
plenty of big vendors
to choose from
data
you probably already
have data for analytics
Retail:CRM – Customer Scoring,Store Siting and Layout,Fraud Detection / Prevention,Supply Chain OptimizationFinancial Services:Algorithmic Trading,Risk Analysis,Fraud Detection,Portfolio AnalysisManufacturing:Product Research,Engineering Analytics,Process & Quality Analysis,Distribution Optimization (GE and Wikibon think manufacturing/industrial growing 2x faster than any other segment: http://online.wsj.com/article/PR-CO-20130618-908554.html)Government:Market Governance,Counter-Terrorism,Econometrics,Health InformaticsEnergy:Smart Grid,ExplorationHealthcare & Life Sciences:Pharmaco-Genomics,Bio-Informatics,Pharmaceutical Research,Clinical Outcomes ResearchAdvertising & Public Relations:Demand Signaling,Ad Targeting,Sentiment Analysis,Customer AcquisitionMedia & Telecommunications:Network Optimization,Customer Scoring,Churn Prevention,Fraud Prevention
http://blog.kissmetrics.com/how-netflix-uses-analytics/“When a network green lights a show, there’s a 35% chance it succeeds and a 65% chance it gets cancelled. At the time of this writing, Netflix has 7 TV shows, of which 5 have been renewed for another season. If this rate can continue for years, the Netflix success rate will be about 70%.”
US leads the globe by about six months.Asia trails the US by about 18 monthsHong Kong trails Asia by about six months
http://www.gov.hk/en/theme/psi/datasets/questions:what is the relationship between traffic and air pollution? (data joining)how does property value lead/trail changes in population (historical analysis)what are the trends for weather-related closures (trending)
http://www.gov.hk/en/theme/psi/datasets/questions:what is the relationship between traffic and air pollution? (data joining)how does property value lead/trail changes in population (historical analysis)what are the trends for weather-related closures (trending)
博文约礼
http://www.gov.hk/en/theme/psi/datasets/questions:what is the relationship between traffic and air pollution? (data joining)how does property value lead/trail changes in population (historical analysis)what are the trends for weather-related closures (trending)
$6.3B in 2012, $48.3B by 2018, CAGR 40.5% (http://www.prweb.com/releases/2013/7/prweb10905352.htm)
