Transcript EMC WITH VMWARE – YOUR JOURNEY TO THE PRIVATE CLOUD

Infrastructures enabling
GRC Insights
CFIT Meeting
Emerging Technologies
Dr. Said Tabet
Senior Technologist, GRC Strategist
Office of the CTO, EMC Corp.
Email: [email protected]
© Copyright 2012 EMC Corporation. All rights reserved.
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AGENDA
• Overview
• Big Data and emerging technologies
– Where it all started
– Big data versus traditional Relational DBs and BI
• Some use cases
• GRC and Big Data
– A new approach to Risk Management
– Compliance as a tool for business process improvement
• The role of standards
• Conclusions
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!!!
“Big Data Is Less
About Size, And
More About
Freedom” ―Techcrunch
!!!
!!!
THE ERA OF
BIG DATA
“Findings: ‘Big
!!! Data’ Is More
Extreme Than
Volume” ― Gartner
IS HERE
!!!
“Total data: ‘bigger’
than big data”
!!!
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― 451 Group
!!!
“Big Data! It’s Real, It’s
Real-time, and It’s
Already Changing
Your World”
!!!
―IDC
3
Our Digital World
Anytime, Anywhere, Any Device
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Living in the Connected Home
Smart Appliances, Smart Phones, Computing
Devices
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Social Media is Changing how the World
Communicates with Each Other
Twitter
Blogs and Websites
Facebook
News
Whatsapp
Weather
YouTube
Weibo (微博)
RenRen (人人网)
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Big Data Architecture(s)
• Big Data is not about Big databases
– Databases cannot support Big data scenarios
• Structured, semi structured, unstructured
• Hadoop, MapReduce
• NoSQL and the next generation datastores
• Optimized for very large data queries
• Hybrid Models: Combine Hadoop and RDBMS
– Leveraging the best of both models
• What works and what doesn’t
– Refining raw unstructured data
– What not to do
– Multiple sources
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Hadoop Overview
• An Apache foundation project: http://hadoop.apache.org
• An open Source Framework implementing MapReduce
• A platform of choice for Big Data Analytics
– used by Google, Yahoo, Facebook, Amazon, and many more in
various industries
• Cost effective, almost every major financial institution has
Hadoop-based projects in place
– However:
• Often operate in silos
• No visibility across products, lines of business, particularly for firms operating in
multiple jurisdictions
– There is a serious need for standards to enable
transparency and interoperability
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The early uses cases
• Google:
–
–
–
–
Search the internet
Web Index
The data is unstructured and very large
Fast parallel processing
Others: Amazon, Yahoo, Facebook (before adopting Hadoop
compared many parallel RDBMS systems)
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Big Data can Generate Significant
Financial Value Across all Industries
Source: McKinsey Global Institute 2011
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IDC Study: The Digital Universe in 2020
• Only a tiny fraction of the world’s Big Data potential is being realized, though the
amount of useful data is expanding
• The digital universe will reach 40 zettabytes (ZB) by 2020, an amount that exceeds
previous forecasts by 5 ZBs, resulting in a 50-fold growth from the beginning of 2010
• Captured where the information in the digital universe either originated or was first
captured or consumed, revealing some dramatic shifts currently underway.
• The amount of data that requires protection is growing faster than the digital universe
itself, yet levels of protection are not keeping pace. 2.8 ZB of data will have been
created and replicated in 2012.
• Machine-generated data is a key driver in the growth of the world’s data – projected to
increase 15x by 2020.
• By 2020, emerging markets will supplant the developed world as the main producer of
the world’s data.
• The investment in spending on IT hardware, software, services, telecommunications
and staff that could be considered the “infrastructure” of the digital universe will grow
by 40% between 2012 and 2020. Investment in targeted areas like storage
management, security, Big Data, and cloud computing will grow considerably faster.
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IDC Study: The Digital Universe in 2020
The proliferation of devices such as PCs and smartphones worldwide, increased Internet
access within emerging markets and the boost in data from machines such as
surveillance cameras or smart meters has contributed to the doubling of the digital
universe within the past two years alone -- to a mammoth 2.8 ZB.
In terms of sheer volume, 40 ZB of data is equivalent to:
• There are 700,500,000,000,000,000,000 grains of sand on all the beaches
on earth (or seven quintillion five quadrillion). 40 ZB is equal to 57 times the
amount of all the grains of sand on all the beaches on earth.
• If we could save all 40 ZB onto today’s Blue-ray discs, the weight of those
discs (without any sleeves or cases) would be the same as 424 Nimitz-class
aircraft carriers.
• In 2020, 40 ZB will be 5,247 GB per person worldwide.
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IDC Study: The Digital Universe in 2020
• Rapid expansion of the digital universe
–
–
Double between now and 2020 to reach 40ZB
Growth in machine generated data a major factor
• Large quantities of useful data are getting lost
–
–
Only 3% of the potentially useful data is tagged, and even less is analyzed
By 2020, 33% of the digital universe (13,000+ exabytes) will have Big Data value if it is tagged and
analyzed
• Much of the digital universe is unprotected
–
–
–
Less than a third of the digital universe required data protection, exceed 40% in 2020
In 2012, while about 35% of the information in the digital universe required some type of data
protection, less than 20% of the digital universe actually has these protections
The level of protection varies by region, with much less protection in the emerging markets.
• A geographic role-reversal is around the corner
Emerging markets accounts for 36% of the universe up from 23% in 2010, to 62% in 2020
• Increased role of Cloud Computing
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Customer Use Case #1
Maximizing Ticket Sales with External Data
Are people more likely to visit the cinema when it’s
raining?
Using advanced data modelling
methods to uncover a nonlinear
relationship between various weather
metrics and average cinema ticket
sales.
There is a ‘sweet spot’ around which
the weather has a positive effect on the
likelihood that a person will want to visit
the cinema.
Promotion emails are now automatically
sent after a period of 3 days of low
pressure which has seen redemption
rates of vouchers soar.
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Customer Use Case #2: Retail Bank
Personalized Digital Safety Deposit Box
How to create more stickiness with existing
customers?
New revenue generating service called “Digital Vault” for
account holders to store their online documents such as
passport photo, birth certificates, legal documents,
personal photos, etc.
Complete Self-Service allowing account holders to sign-up
directly from Bank Portal, and can retrieve and upload
content from any mobile device.
Priced at USD$5/month for 200GB, and USD$10/month
for unlimited storage.
Net-new annual revenue stream of USD$3M from “Digital
Vault”.
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Customer Use Case #3
Customer Profiling – “Map of Me”
Can understanding the social profile of consumers increase sales?
Insurance company wants to leverage strong consumer profiling capabilities by
correlating survey data, previous purchasing behaviour, social media consumption and
engagement habits to better understand their target consumer.
 The goal is to tailor additional up-selling and cross-selling
opportunities.
By using Advanced Social Analytics solutions, they are able to create a personalized
“Map of Me” profile for each customer. This “Map of Me” will evolve over time as the
customer continues to interact with agents representing the insurer.
 These are live customer profiles
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Customer Use Case #4
World’s First Capital Market Community
Platform
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Connecting to the Global Capital Markets
Community via Cloud-based Liquidity Centers
Total market cap of listed companies: $24
GDP
of the United States: $14.7 Trillion
trillion
Messages processed per day: 1.4 billion
Total Google Searches per day: 400 million
Transactions executed per day: $2.5 trillion
eBay Transactions per year: < $500 billion
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New Market Opportunities for NYSE
Technologies
to Drive Revenue
through
Cloud
and Big Data
Market
Data
On-Demand Multi-time
Warehouse as a Service
Zone Trading
Infrastructure as a
Service
On-Demand Regulatory Services
(e.g. WORM drive transaction
recording)
Storage as
a Service
Compute as
a Service
NYSE Exchange
Community Cloud
On-Demand Proximity
Low Latency Trading
On Demand Geographical
Transaction Recording
Services
Reporting Data and
Analytics Services
Securities Exchange
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Position Management & Real-time Pricing
Threshold Detected
Market Data
Position
Trades
Real-Time Update
Bids
Risk
Factors
Offers
Historical & End-of-Day Data
Big Data Analytics Enables Low-latency Operational and Risk
Analysis
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Trend Analysis and Pattern Detection
Trend Detected
Data Models
Small Grain, Continuous
Streaming Data
Counters &
Accumulators
Fast Active Data
•
•
•
•
•
•
Market Forecasting
Insider Trading
Anti-Money Laundering
Fraud Detection
Trade Surveillance
…
Trend Validated & Details
Big Historical Data
Big Data Analytics Enables Risk Mitigation and Behavioral Prediction
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Governance, Risk, and
Compliance
in the era of BIG Data
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Enterprises today: The Problem
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A Transformational Opportunity For All Stakeholders
SOURCE: OCEG Illustrated Series
SOURCE: OCEG Illustrated Series
Current State
Future State
•
Fragmented silos
•
Integrated management & performance
•
Mostly reactionary
•
Proactive planning & execution
•
Individual projects
•
Integrated capability
•
Separate from mainstream processes
and decision-making
•
Embedded within mainstream processes and
decision-making
•
Spreadsheets, spreadsheets, spreadsheets
•
Coordinated transactions & shared data
•
Limited and fragmented use of technology
•
Architected solutions
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Market Landscape and Big Data
Relevance
CIO Priorities
–
–
–
–
Improve customer experience (big data analytics)
Predictive modeling and BI to drive new business (advanced analytics)
Achieve and maintain regulatory compliance (actively deal with risks)
Process efficiencies to help grow the business (more accurate BPM)
• Top IT Investment Areas
– Distribution channels
• Customer, agent, and partner automation
– Data analytics for risk management and new business/improved
products
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Compliance Challenges
• Complex and evolving regulatory environment in multiple
jurisdictions
• Understanding and demonstrating relationships between
company objectives, risks, internal controls, and external
influence
• Establishment of a consistent control evaluation, testing
and monitoring
• Demonstrating accountability and progress of issue
remediation activities
• Rapid onset of new technologies
• Coordinating with supporting assurance functions
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Governance, Risk and Compliance
GRC Program Oversight
• Requirements are not new, but
have expanded
• Automation and standardization
is a trend and opportunity
• Historically required of Managed
Service Providers (MSP):
– IT Service Level
Agreements with
metrics
• IT Service Management
• Business Continuity
– Compliance certification
against a framework
such as ISO27001/2
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Risk Management in the era of Big Data
•
•
•
•
Accurate and timely risk management
Leverage data from across the business
Compare it to data from the markets or other data sources
Relational systems can’t deal with very large unstructured
datasets
• Regulatory requirements in many jurisdictions pushing for
transparency and enterprise risk management
• Need for financial institutions to integrate GRC into mainstream
processes
• Performance driven compliance management
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OCEG Open Risk Universe
 Nature
External



Macro Environment

Natural disaster
Weather
Pandemic
 Society


 Politics
Social requests
Demographic
Cross-border
Cross-sector
 Governance
Management Oversight
Internal
Vision/Mission
Competence assessment
Capability/Capacity assessment
Alliance
Merger & acquisition
Planning
Culture
Quality/Customer satisfaction
Business disruption
Product development
Production capacity
Product/service deficiency
Operation error
 Financial






Competition
Customers/Consumers
Investors/Lenders
Trading partners
Affiliates
Government
Reputation


 Effectiveness/Efficiency
Liquidity
Credit
People/Organization
 Corporate culture
 Ethical behavior
 Effectiveness of
the board







Brand Image
Stakeholder relationship
Process






 Strategy







Energy technology
innovation
Production
Innovation
IT innovation
Environment technology
innovation


Business condition
Price of goods
Price of materials
Market condition (currency, interest rate, etc.)




Decision Making


 Economics
 Regulations


 Technology
Change of
administration
Legislation
Public policy


Micro Environment
Labor capability
Labor sincerity
Authority/Limit
Intellectual property




 Compliance




Law violation
Privacy protection
Information control
Social Imperative
 Reporting




Financial reporting
Tax reporting
Environment conservation
Regulator reporting
Technology
Effectiveness
Efficiency
Confidentiality
Integrity
 Availability
 Compliance
 Reliability
Copyright , OCEG 2012
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Why do we need Standards?
• Use of available technical expertise, enhanced trade
• Common metrics for service level expectations
• Essential to the cloud supply chain
• Open global markets
• Required by legal and accounting professions
• Increased automation
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