Helping Compliance Cross The Data Chasm

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Helping Compliance Cross the Data Chasm

Welcome to Compliance Week’s virtual conference on Big Data and how compliance can respond to the emerging risks.

This afternoon’s Webcast will feature Mario Faria, data strategist with Boa Vista and will explore some real life compliance tools for crossing the data chasm.

The discussion will be hosted by Compliance Week Executive Editor, Joe McCafferty.

You can submit questions to our speaker by using the “Ask a Question” button on the left side of your screen.


This Webcast will last for 50 minutes

1:30 p.m. Introduction Joe McCafferty, Compliance Week

1:35 p.m. Discussion Mario Faria, Boa Vista

2:05 p.m. Q&A: Will be kept anonymous

2:20 p.m. Closing Remarks: From Compliance Week

Agenda for Today’s Webcast



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Visit our website for future virtual event dates and topics www.complianceweek.com Instructions:

Use the “Ask A Question” function (left side of your screen) All questions will be anonymous.

Introduction: The Series, Schedule & Instructions


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• Has worked as a CDO for Boa Vista, a credit bureau services provider in Brazil, which is partly owned by Equifax.

• Is a professor of marketing and strategy at the MBA program of the Business School São Paulo (BSP).

• Is a contributor of several conferences, magazines and publications in areas of Big Data, Data Analytics, Data Management, Digital Marketing, Social Media, and Technology.


Today’s Presenter

Mario Faria Data Strategy Advisor, Boa Vista

Mario Faria

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Helping Compliance Cross

the Data Chasm

March 27th, 2013

Mario Faria

Data Stratagy Advisor

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Objectives of this seminar

• To help Compliance people to understand what is currently happening with data and technology

• To present some Big Data concepts that will help Compliance people do their jobs better

• To provide insights on how Compliance and Data Teams should successfully work together inside an organization

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Who am I ?

• MIT recognition as the 1st Chief Data Officer and Lead Data

Scientist of Latin America

• 20+ years working with Information Technology,

Management Consulting, Financial Services, Retail,

Consumer Goods and Private Equity

• Expertise in Data Management, Analytics and BI at Boa

Vista (Equifax Joint Venture), IBM, Accenture and Microsoft

• Speaker at several conferences on these subjects in USA and throughout Latin America

• Contributor writer for magazines and publications in areas of data management, marketing, media and technology

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Our agenda today

• How we got here

• The 5 waves of Technology

• From BI to Big Data

• The Data Life Cycle

• The Chief Data Officer / Head of Analytics / Data Scientists

• Is Big Data a threat or a tool for Compliance ?

• Going from here

• Conclusions

• Q&A

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There was a time in history of

mankind …

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On Compliance and Big Data

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Compliance and Big Data : more

than 38 million results

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Compliance and Big Data : more

than 1.8 million results

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How to make sense ?

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Helping Compliance Crossing the

Data Chasm

Geoffrey A. Moore

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How we got

here in terms of

Big Data

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Web 1.0

Bricks to Clicks

The Web Evolution : more and more

data driven

Web 2.0

Participatory

Web 3.0 - Data-driven

Web moves from broadcast (push) medium

to enabling two-way dialogue based on:

- Behavior

- Preferences

- Profile data

- Personalized user experiences

Leverage the web as a database

- Machine learning

- Predictive analytics

- Automated modeling

Internet of things

- Widgets

- Peer-to-peer networks

- Devices, cars

Middle 90s 2005 - 2011 2012 moving forward

http://www.ebay.com/

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The 4 driving factors that are

changing the technology industry as

we know it

• Social

• Mobile

• Cloud

• Information

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The 5 Waves of

Technology

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The 5 waves of computing technology

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1st wave - computers

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2nd wave - ERPs

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3rd wave – CRM and Supply Chain integration

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4th wave – Business Intelligence

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5th wave – Social Computing

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From Business

Intelligence to

Big Data

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What is Analytics ?

“The extensive use of data, statistical

and quantitative analysis, explanatory

and predictive models, and fact-based

management to drive decisions and

actions” – Thomas Davenport

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Analytic Maturity Curve

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SQL

MAPREDUCE

HADOOP

CLOUDSCALE

MPI

BSP

PREGEL

DREMEL

PERCOLATOR

What is Big Data?

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Differences between Big Data and Traditional BI projects

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The evolution path to Big Data

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Big Data is not just about : • Large volumes

• Greater scope of information

• Real time access to information

• New kind of data and analytics

• Data influx from new technologies

• Non-traditional forms of media

• Variety of sources

It all of the above, plus a transformation in processes and

culture, and it is a disruptive factor for entire industries

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Analytics is about customer centricity

• Supply Chain forecasting

• Behavioral analysis

• Operations improvement

• Marketing targeting / decisions

• Real-time pricing / promotions

• Customer experience analysis

• Customer insights

• Customer lifecycle management

• Fraud prevention and analysis

• Network monitoring

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Big Data & Analytics are transforming

how companies operate, internally and

externally, at startling speed

• Big Data = Big Problem

• The change in employee norms is challenging traditional corporate hierarchies

• The really big headache for companies is how to break down internal “silos” of information

• Tomorrow’s corporate winners will be the businesses that can not just collect numbers but make sense of them too, and find ways to use this data to foster more collaboration across the organization

Sir Martin Sorrell,

CEO WPP,

@ Davos World

Economic Forum

Jan 2013

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Big Data

=

Human Behaviour

The

Data Life

Cycle

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Some problems, at this point, in

most organizations

• Data is fragmented and scattered

• Like the truth, data has many versions

• The Data Lifecycle is a complex process

• A formal process to manage data is a

requirement in order to do Analytics

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The complexity of the Data Life Cycle

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Usage of wrong data can make you

lose money

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Usage of wrong data can destroy

credibility

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Who owns the Data inside an

organization ?

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Chief Data Officer /

Head of Analytics /

Data Scientists

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More and more, data leaders are being hired

to think strategically think about all the steps

from getting raw data and making it useful to

business users

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Chief Data Officer (CDO) /

Chief Analytics Officer (CAO) /

Lead Data Scientist

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Chief Data Officer (CDO) /

Chief Analytics Officer (CAO) /

Lead Data Scientist

• A new profession that is becoming very common in

corporations

• He/she is a corporate officer who is the business

leader for enterprise-wide data processing and data

mining.

• The CDO typically reports to the CEO or the COO

and is a member of the executive management team

of a company or business unit.

• CDOs leverage their organization's data assets in

support of strategy. He/she manages enterprise-wide

data administration and is the champion of enterprise

information management

• CIOs are concerned with this new role, because of

the threat to their current status quo

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The role of a Chief Data Officer or

Lead Data Scientist

A data scientist is the one

who looks for insights

The insight is operationalized

in BI/DW products, by data architects

The insight is shared

with the enterprise The CDO or Lead Data Scientist is the

executive responsible and accountable for

the data life cycle inside the organization,

managing the people involved in the data

activities, such as acquisitions, analytics,

processes, governance, quality, technology

and budget

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Why do you need Chief Data Officer ?

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Why do you need a

Chief Data Officer ?

• Data is about business, it's not about IT

• Data is an economic asset, so you

need a senior person to handle the

data initiatives.

• As an economic asset, data needs:

control, show value and monetization

• There is now way you can do

Advanced Analytics unless you have

some data management practices in

place.

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How a CDO should implement

Big Data projects

• Define what Big Data means to the organization

• Establish a data-driven culture inside the business units

• Adopt the most-suited technologies of business rules

• Put in place predictive analytics to build decision systems

that are agile, analytic and adaptive

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The Predictive Analytics Process Must Be Continuous To Ensure Effectiveness

January 2013 “The Forrester Wave™: Big Data Predictive Analytics Solutions, Q1 2013”

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Foundations of the Big Data team

responsibilities

• Data Strategy

• Data Analytics

• Data Insights

• Data Architecture

• Data Governance

• Data Quality

• Data Acquisitions

• Data Operations

• Data Policies

• Data Security

• Data Protection

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Wait a second !

Compliance means conforming to a

rule, such as a specification, policy,

standard or law

It reminds a lot of what the data guys

call DATA GOVERNANCE

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There is, after all, a strong tie

between Compliance and the

foundations of Big Data

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Is Big Data

a threat or a tool

for Compliance ?

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Compliance and Big Data risks

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A threat

for Compliance ?

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LAST summer, employees at the National

Aeronautics and Space Administration received an

in-house newsletter illustrated with mock front

pages of USA Today and The Washington Post and

seemingly hyperbolic headlines like: “NASA Laptop

Stolen, Potential Compromise of 10,000 Employees’

Private Information!” – extract from NY Times, Feb

16th 2013

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The Companies and Countries Losing Their

Data, by Sarah Green, March 12, 2013, HBR

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The Companies and Countries Losing Their

Data, by Sarah Green, March 12, 2013, HBR

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One Big Data usage : Social CRM and

Behavioral Targeting

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Gaydar Project - MIT

• Finding out sexual

orientations

• Facebook posting analysis

• Friends lists identifications

• Behaviour patterns

• Inferences and predictive

analysis

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Facebook 'likes' can reveal your secrets According to a new study from the University of Cambridge, it’s possible to predict a person’s private traits — sexual orientation, political leanings, religion, intelligence, etc. — just by analyzing their Facebook likes. Researchers looked at the FB profiles, likes, surveys and personality tests of 58,466 individuals, and from that data developed a model that predicts personal attributes with a great deal of accuracy. www.cnnn.com/2013/03/11/tech/social-media/facebook-likes-study/

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The Big Data Fragmented Tech Vendors : data life cycle

process view

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Technology alone will not change the

previous results

To succeed in Big Data, an organization will be required to

change some of its current internal processes

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The complexity of an Analytics

project

• It requires a better, more robust and scalable infra-

structure

• A new way of thinking about architecture

• More deployment options

• Changing patterns of data consumption

• More complex data management requirements

• Data demands from more applications

• Data Integration will be a critical path of the project

• Pressure for faster results

• Different needs and roles after the project goes live

(it requires change management and processes

reconfiguration)

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The catch : just a few companies (users and

consulting) understood the nits and grits

about Big Data Analytics: it requires you to

moving from a data management vision

(tactical) to an information management

vision (strategic)

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A requirement for any Big Data project

• Any Big data initiative is very dependent upon a scalable

and extensible information foundation

• Some companies may not have them at home (on

premises) and will require a cloud solution to deploy

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A tool

for Compliance ?

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Big Data for Network Security Monitoring

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A real case from a financial services institution

• Compliance Team using Big

Data tools to Analysing emails

and unstructured context

documents much faster

• Using machine learning to

speed up the recognition of

false positives / true negatives

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Using Big Data for Fraud Management in Healthcare

Healthcare Fraud Management using Big Data Analytics, by Trendwise Analytics,

http://trendwiseanalytics.com/

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Going from here

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The main drivers for

Data/Big Data projects

• Make more money

• Reduce current costs

• Improve efficiency

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What it takes to make Big Data projects

drive results

• Data – understand what they have and how to be creative when it comes to using internal and external data

• Models – focus on developing models that predict and optimize

• People – transform their organizations with tools and effective training so that managers can take advantage of Big Data's insights.

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Conclusions

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What Compliance has to

understand about Big Data

• Big Data projects are happening

• Where the data is coming from

and where it is heading

• Who is using it, how it is being

used, why it being used and when

it is being used

• How it is stored

• How/If it is being disposed

• Security and privacy and issues

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Data and Compliance Teams should

be able able to work together on Data

issues related to Governance,

Policies, Security and Protection

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• How we got here

• The 5 waves of Technology

• From BI to Big Data

• The Data Life Cycle

• The Chief Data Officer / Head of Analytics / Data Scientists

• Is Big Data a threat or a tool for Compliance ?

• Going from here

What we have seen today

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“Business are complex systems,

optimizing a single element rarely

creates lasting value”- Peter Drucker,

the father of modern management

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I have learned how to work with

Compliance people. And it did

help me, as a data leader, to

achieve my goals

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Q&A

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Thank you

Mario Faria Data Strategy Advisor

http://www.linkedin.com/in/mariofaria/

Founder of the Digital Mad Men

www.slideshare.com/fariamario

Twitter : @mariofaria

[email protected]

(425) 628-3517


Mario Faria Data Strategy Advisor, Boa Vista Joe McCafferty (Moderator) Executive Editor, Compliance Week


Question & Answer Session


Feedback Please send to: [email protected] Thanks Mario Faria, Data Strategy Advisor, Boa Vista

*CPE Credit

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Documents

Helping Compliance Cross The Data Chasm