31 липня у "Часописі" відбулася зустріч із Олександром Романко, старшим науковим співробітником канадського представництва IBM, професором Університету Торонто.

1. Наші у … IBM
Oleksandr Romanko, Ph.D.
Senior Research Analyst, Risk Analytics – Business Analytics, IBM
Adjunct Professor, University of Toronto
Chasopys, Kyiv
July 31, 2015

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Please note:
IBM Risk Analytics statements regarding its plans, directions, and intent are subject to
change or withdrawal without notice at IBM’s sole discretion.
Information regarding potential future products is intended to outline our general product
direction and it should not be relied on in making a purchasing decision.
The information mentioned regarding potential future products is not a commitment,
promise, or legal obligation to deliver any material, code or functionality. Information about
potential future products may not be incorporated into any contract. The development,
release, and timing of any future features or functionality described for our products
remains at our sole discretion.
Performance is based on measurements and projections using standard IBM benchmarks
in a controlled environment. The actual throughput or performance that any user will
experience will vary depending upon many factors, including considerations such as the
amount of multiprogramming in the user's job stream, the I/O configuration, the storage
configuration, and the workload processed. Therefore, no assurance can be given that an
individual user will achieve results similar to those stated here.

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About me
Dr. Oleksandr Romanko
 Senior Research Analyst, Quantitative Research at Risk Analytics,
Business Analytics, IBM, with the company since 2010
 Ph.D. in Computer Science from McMaster University
 Author of over 20 papers and reports
 Adjunct professor at University of Toronto
and lecturer at McMaster University
 Was Mitacs Elevate Industrial Postdoctoral
Fellow
 Research areas:
 operational research, optimization, finance
 portfolio optimization, multi-objective optimization
 market and credit risk modeling and optimization
 numerical methods for risk management
 design of numerical algorithms and their software implementation

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Quick facts about IBM Risk Analytics (formerly Algorithmics Inc.)
Algorithmics offers risk solutions, software and advisory services for
– Banking
– Insurance
– Asset Management
– Hedge Funds
– Pension Funds
Founded in 1989
Acquired by IBM in 2011 for $387M USD
Over 800 employees worldwide
– 200 in Research and Development
– 250 in Professional Services
– 110 in Business Lines
Head Office in Toronto
– Primary offices in London and New York
– 23 offices globally in all major financial centers
– Clients in 55 countries
2010 revenue over $163M USD

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Some of our clients

6.  Being an IBMer

7. 7
IBM Centennial: A Century of Progress
1911
2011
Incorporated on June 16, 1911 in US as the
Computing Tabulating Recording Company
CTR changed its name to International
Business Machines Corporation
globally in 1924
CTR changes name in Canada to International
Business Machines Company in 1917

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Making the world work better – pioneering the science
2008
19731969
1981

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IBM Centennial: 100 Years of Innovation

10.  Business Analytics

11. Predictive Analytics
What will happen?
Descriptive Analytics
What has happened?
Prescriptive Analytics
What should we do?
What is analytics?
Data Insight Action
DecideAnalyze
Business Value
11
Analytics is the scientific process of deriving insights from
data in order to make decisions

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Applications of big data analytics
Homeland Security
FinanceSmarter Healthcare Multi-channel
sales
Telecom
Manufacturing
Traffic Control
Trading Analytics Fraud and Risk
Log Analysis
Search Quality
Retail: Churn, NBO

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History of business analytics

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History of business analytics

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Movies

16.  Business Analytics
Examples

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Smarter Cities

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Use of camera phones at the Papal inauguration in 2005 and 2013

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We can collect information from almost everything to make better decisions
Camera phones in
existence able to
document accidents,
damage, and crimes
1 billion
RFID tags
embedded into our
world and across
entire ecosystems
30 billion
Of new automobiles
will contain event data
recorders collecting
travel information
85%
Instrumented Interconnected Intelligent

20. Pit stop analytics
7
Calculations showed that time spent changing tires and refilling the tank was more
than offset by the improved performance of the car on the track.
1. Softer tires stuck to the track better during turns than their harder cousins,
though they wore out more quickly.
2. Less gas in the tank translated into a lighter, and therefore faster, car.
Optimized F1 pit teams can change four tires in two seconds

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Artificial intelligence
Source: A Brief Overview and Thoughts for Healthcare Education and Performance Improvement by Watson Team

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Artificial intelligence
Source: A Brief Overview and Thoughts for Healthcare Education and Performance Improvement by Watson Team
On 27th May 1498, Vasco da Gama
landed in Kappad Beach
On 27th May 1498, Vasco da Gama
landed in Kappad Beach
celebrated
May 1898 400th anniversary
arrival
in
In May 1898 Portugal celebrated
the 400th anniversary of this
explorer’s arrival in India.
Portugal
landed in
27th May 1498
Vasco da Gama
Temporal
Reasoning
Statistical
Paraphrasing
GeoSpatial
Reasoning
explorer
On 27th May 1498, Vasco da Gama
landed in Kappad BeachOn the 27th of May 1498, Vasco da
Gama landed in Kappad Beach
Kappad Beach
Para-
phrases
Geo-
KB
Date
Math
India
Search Far and Wide
Explore many hypotheses
Find Judge Evidence
Many inference algorithms

23.  IBM Educational
Initiatives

24. IBM Academic Initiative program
Cognos SPSS ILOG

25. Master of Business Analytics programs – top 20 universities

26. Industry support for Master of Business Analytics programs

27. Industry support for Master of Business Analytics programs

28. Example analytics degree programs with university partners

29. Master of Business Analytics programs – curriculum
 Прикладная статистика и теория вероятности (Applied Statistics and
Probability)
 Основы вычислительной математики (Fundamentals of Computational
Mathematics)
 Интеллектуальный анализ данных и эксперные системы (Data Mining and
Knowledge Discovery)
 Имитационное моделирование (Simulation Modelling)
 Оптимизация (Optimization)
 Вычислительные финансы и риск менеджмент (Computational Finance and Risk
Management)
 Визуальная аналитика и представление знаний (Visual Analytics and
Knowledge Representation)
 Математическое моделирование в бизнесе (Mathematical Modelling for
Business)
 Аналитика в маркетинге (Marketing Analytics)
 Стратегии менеджмента инноваций (Strategies for Managing Innovations)
 Аналитика Интернета, социальных сетей и бизнес новостей (Analytics of Web,
Social Networks and Business News)

30.  Analytics Consortium

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Analytika PH
http://newsbytes.ph/2014/04/22/consortium-launched-to-make-ph-as-global-analytics-hub-by-2015/

32.  Online Education

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Online education – Coursera, EdX, Prometheus

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Online education - Big Data University (bigdatauniversity.com)
 Flexible on-line delivery allows learning
@your place and @your pace
 Free courses, free study materials.
 Cloud-based sandbox for exercises –
zero setup with Robust Course
Management System and Content
Distribution infrastructure
 169,000 registered students.
 Free IBM Hadoop, BigInsights
Publications

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TED and TEDx

36.  Startups

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Ecois.me

38. 38
Nymi

39.  Volunteering and
Networking

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Networking

41.  Ukrainian Diaspora
in Canada

42. EuroMaidan Canada

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Questions