MGI Big Data :
The next frontier for innovation,
competition, and productivity
2011-09-19
Jimin Lee
jmlee@mmlab.snu.ac.kr
2/19
Outline
•
•
•
•
•
•
What is Big Data?
Why Big Data is important?
Examples and value evaluation
Big Data techniques and technologies
What should we prepare for Big Data era?
Conclusion
3/19
What is Big Data?
• Definition
– Datasets whose size is beyond the ability of
typical database software to store, manage, and
analyze
• Recently, various economic journal and
consulting group have significantly
reported and analyzed Big Data
– Economist (2010.05)
– Gartner (201103)
4/19
What is Big Data?
• Companies are tracking and collecting
the customer data
• Multimedia contents and usage of
contents are increasing
• Social media is producing a tremendous
amount of new data
5/19
Why Big Data is important?
• We are already living in zettabytes world!
– In 2009, 800 exabytes (0.8 zettabytes)
– In 2010, 1.2 zettabytes
• Data is being produced now!
6/19
Why Big Data is important?
• The growth of big data is a phenomenon
that we have observed in every sector
7/19
Why Big Data is important?
• Big Data is essential resource of mobile
smart innovation
Input
Industry
Revolution
IT
Revolution
Iron, Coal
Internet
Mobile
Smart
Innovation
Big Data
Usefulness
output
Customer analysis, market demand prediction
Innovation
Cost cut, different product
Competition
Industry-wide increasing productivity
Productivity
8/19
Innovation
• O2 provides Starbucks promotion for
mobile customer by analyzing Big Data
with ‘SNS + LBS’
• Facebook Immediately provides target
customer with advertiser
– CM Photographic co.
SNS : Social Network Service
LBS : Location Based Service
Competition
• public access to analysis and transparency of
management of organization
– Big Data analysis is open to external partners
– The sophistication of data analysis and real-time data
processing
– Collaborative management of
organization's competitiveness by improving
transparency
• Walmart
– Retail Link
• Real-time analysis of inventory
10/19
Productivity
• Health care
– The estimated long-term value of
Direct/unclear impact is more than $300
billion
Potential advantage of
industry sector
12/19
Demand of analytical talent
• Supply and demand gap for three types
of Big Data talent in 2018
– Additionally 140,000~190,000 relevant
people are needed
13/19
Summary of section
14/19
Techniques and Technologies
• Cloud Computing
– Fast and flexibility, and provide economies
of scale
– Approximately 35% of data in the cloud or
go through the cloud
– Cloud can be challenge for companies
• Hadoop, MapReduce software
15/19
Techniques and Technologies
• Real-time analysis
– Analyzing SNS and Internet boards in realtime can provide a significant opportunities
– To derive customer satisfaction issues
• Can run next best offer
– Companies improve service by using SNS
data to be reflected quickly in real time
• Coca-Cola co.
16/19
What should we prepare
for Big Data era?
• Maintenance of internal organization is
required for internally using Big Data
– Currently, most company’s data is distributed by
division
– Not a problem in a particular department,
enterprise-wide perspective
Condition
Key issues
Preparation
Data access
Third-party data utilizing,
combining the internal/external data
Privacy, security and
preparing the legal liability
Big Data infra
Cloud-based integrated analysis system
integration of distributed
Data
Organization
Expert analysis, professional workforce
Recruiting specialists
17/19
What should we prepare
for Big Data era?
• National-wide plans to enhance national
competitiveness
– When Big data is utilized in public sector
• Provides transparency and openness, and high
levels of productivity and operational efficiencies
18/19
Conclusion
• Big Data era is coming
• Many companies can utilize BD-value
cases, and provide effective results
• Techniques
– Cloud computing
– Real-time analysis
• Enterprise-wide and national-wide
preparation is required
19/19
Appendix
20/19
Appendix
• Hadoop
21/19