June 15, 2013

AXEOR and IBM Present…

Capitalize on the Power of Big Data to Transform

Marketing

Presented by: Nick Kabra, Advisor to Axeor and IBM Big Data Practice

The Big Question about BIGGGGGG DATA:

BIG data is a big buzzword to make big

money by solving seemingly BIG …..

PROBLEMS….

The 6Vs…. Can there be more…

Volume

Velocity

Variety

© 2013 IBM Corporation 2

Veracity

Visualization

Value

3

By BRUCE BARTLETT, The Fiscal Times

June 14, 2013

Ever since former CIA employee Edward Snowden leaked information about the top secret PRISM

program – a government system for monitoring vast amounts of electronic data – people have been

asking what, exactly, the government does with all that data.

Read more at http://www.thefiscaltimes.com/Columns/2013/06/14/Is-PRISMs-Big-Data-about-Big-

Money.aspx#SuEj0mSZMJuXXFhw.99

NSA PRISM

4

APPLICATIONS……

5

•Big Data in Dodd Frank reporting-

•5 years data to be saved, USI, LEI, UPI, UCI – no format.

•Reproduce the data in specific time for authorities

•How do you report to DCM, SEF, DCO

•Different reporting formats for SEC, CFTC, FED and newly formed

•Data to be sent to SDRs, SEF in different formats and fields

•FATCA

Dodd-Frank Act… Volcker… FATCA

6

Insights for Valuation

Building an investment recommendation platform

Make investment recommendations and investment decisions

Twitter and FB feeds, Hoovers online

Equity /Bond research houses

Kiplinger, the street, finviz, smartmoney, seeking alpha

Bloomberg, Reuters, Telekurs, Telerate, Markit,

Used Tableau, Pentaho, Platfora, Acunu, Elastic Search for

filtering, heat maps, Pareto chart, cascading filters and co-

relations. Find the outliers. Recommend to hedge funds in

real-time. Used Drill.

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Trading, Risk, Regulatory Reporting

Discovery-to-Decision Making using operational insights with

minimal latency via visualization

This program is a convergence of BIG data, data discovery, business

intelligence and analytics.

Implement a common trade and asset representation across all asset

classes and functions.

It includes end-to-end trade capture through risk management to the

subledger as a “Single Source of Truth”.

Architecting, Designing and Implementation using data collection, Hadoop,

messaging, algorithms, analytics and visualization technologies.

The END GOAL…

8

Too Many/MUCH of EVERYTHING… BOMBARDMENT???

Too many Databases, too many technologies, too many tools,

too many analytics methods…

?????

9

SO WHERE DO YOU START

Technical Requirements

Consider the Cloud

What hardware you need

*Master Node and Secondary Master Node

*Slave Nodes

*Network, RAM, CPU, Application server, Power and utility costs etc

What software will you need

Unix system (Redhat, Ubuntu, CentOS etc.)

JVM or JRE

Apache Hadoop (packaged version from Cloudera, MapR,

Hortonworks, Big Insights or plain vanilla

NOSQL and Columnar database (from among the 150 odd) –

Cassandra, MongoDB, Accumulo, Riak, neo4J, hypergraphDB,

orientDB,

Analytics DB– Teradata, netezza, greenplum etc

MySQL database – for queries

Analytics – Descriptive, predictive, prescriptive

10

SO YOU Decided… NOW WHAT….Scoping your Big DATA Engagement

Identify the use case – Proof of Value

Identify the team

*You need senior management support – someone powerful

*Decision makers and Business owner, budget

*Line of Business- PM, Data owner, SME

*Tech team-infrastructure head, hadoop admin, security, DB team, BA, PM, architect, developer,

QA

Identify the data sources

Size the H/W, Cluster, Cloud, Replication etc.

Stakeholders buy-in, project plan, evangelize, risk assessment

Deploy –H/W, S/W, network, monitoring –Ganglia or Nagios, security, DB, BCP

Collect Data – from data sources, connectors, push or pull, data aggregation, integration,

Visualization -Use various tools or build your own(Make/buy), annotations, extensible, ease of use

Analytics – Descriptive, predictive, prescriptive, A/B

Deepen Insights- Go-live, Find outliers, drill deeper, iterations, interpret root causes, validate results

Measure ROI – trends, performance, ROO, RONS

Example Problem: Marketing Campaign

Jane is an analyst at an e-

commerce company

How does she figure out good

targeting segments for the next

marketing campaign?

She has some ideas… …and

lots of data

User

profiles

Transaction

information

Access

logs

Traditional System Solution 1: RDBMS

ETL the data from

MongoDB and

Hadoop into the

RDBMS– MongoDB data must

be flattened,

schematized, filtered

and aggregated

– Hadoop data must be

filtered and aggregated

Query the data

using any SQL-

based tool

User

profiles

Access

logs

Transaction

information

Traditional System Solution 2: Hadoop

ETL the data from Oracle and MongoDB into Hadoop– MongoDB data must be

flattened and schematized

Work with the MapReduce team to write custom code to generate the desired analyses

User

profiles

Access

logs

Transaction

information

Traditional System Solution 3: Hive

ETL the data from

Oracle and MongoDB

into Hadoop– MongoDB data must be

flattened and

schematized

But HiveQL queries

are slow and BI tool

support is limited– Marshaling/Coding

User

profiles

Access

logs

Transaction

information

What Would Google Do?

Distributed

File System

Batch

processing

Interactive

analysisNoSQL

GFS MapReduce Dremel BigTable

HDFSHadoop

MapReduce??? HBase

Build Apache Drill to provide a true open

source solution to interactive analysis of Big

Data

Why Apache Drill Will Be Successful

Resources

• Contributors have

strong backgrounds

from companies like

Oracle, IBM Netezza,

Informatica, Clustrix

and Pentaho

Community

• Development done in

the open

• Active contributors

from multiple

companies

• Rapidly growing

Architecture

• Full SQL

• New data support

• Extensible APIs

• Full Columnar

Execution

• Beyond Hadoop

Bottom Line: Apache Drill enables NoSQL and SQL Work

Side-by-Side to Tackle Real-time Big Data Needs

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Vertical and Horizontal Domains

18

Some Current Applications

Some Current Applications

Vertical Refine Explore Enrich

Retail & Web• Log Analysis

• Ad Optimization

• Cross Channel Analytics

• Social Network Analysis

• Event Analytics

• Dynamic Pricing

• Session & Content

Optimization

• Recommendation Engines

Retail• Loyalty Program

Optimization

• Brand and Sentiment

Analysis

• Dynamic Pricing/Targeted

Offer

Intelligence • Threat Identification • Person of Interest Discovery • Cross Jurisdiction Queries

Finance

• Risk Modeling & Fraud

Identification

• Trade Performance

Analytics

• Surveillance and Fraud

Detection

• Customer Risk Analysis

• Real-time upsell, cross

sales marketing offers

Energy• Smart Grid: Production

Optimization

• Grid Failure Prevention

• Smart Meters• Individual Power Grid

Manufacturing • Supply Chain Optimization • Customer Churn Analysis• Dynamic Delivery

• Replacement parts

Healthcare &

Payer• Electronic Medical Records

(EMPI)

• Clinical Trials Analysis

• Supply Chain Optimizations• Insurance Premium

Determination

Page 2

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APPENDIX……

20

Retail BankingConsumer Lending/

Card ServicesCommercial Banking

Investment Banking/

Asset ManagementInsurance

Market Mix Modeling

Acquisition and

Behavioral

Scorecards

Credit Risk

Management

Asset Liability

Matching

Pure Premium

Modeling

Customer

Satisfaction &

Experience

Collections

Management

Stress Testing and

Scenario Analysis

Portfolio

Optimization

Price Optimization

Management

Credit Risk

Management

Market Research

Analytics

Market Research

Analytics

Interest Rate Risk

Management

Catastrophe

Management &

Reinsurance

Channel

Optimization

Call Center

Optimization

Daily/Weekly Risk

Measurement and

Reporting

VaR Modeling Loss Modeling

Portfolio Stress

TestingWeb Analytics

BASEL Compliance /

Monitoring

Regulatory

Compliance

Agency Incentive

Compensation

Customer Lifetime

Value

Fraud Management

Tools

Pricing Collateralized

DebtLapsation Modeling

Cross-sell Targeting

Banking

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Customer

AcquisitionCRM Marketing

Risk

ManagementOperations

Fraud Control &

CollectionCard Services

Product Feature

Selection

Customer

Life Time Value

Market

Profiling &

Sizing

Behavioral

Scorecard

Staffing

Analysis

Collections

Scorecard

Merchant

Performance

Scorecard

Product Pricing

Offer

Optimization /

Customization

Market Mix

Optimization

Risk Based

Pricing

ATM/Branch

Positioning

Delinquency

and Roll

Rate

Analysis

Merchant Fraud

Modeling

Acquisition

Scorecard

Customer

Loyalty

Tracking

Market Spend

Optimization

Credit / Market

Risk Evaluation

Financial

Reporting

and

Analysis

Payoff /

Foreclosure

Analysis

Merchant

Acquisition

Cross Sell

Response

Models

Churn / Attrition

Analytics

Promotion

Effectiveness

Portfolio Health

Tracker

Channel

Process

Management

Self-cure

Propensity

Analysis

Merchant

Retention

Analysis

Segmentation

and Targeting

Customer

Experience /

Value

Customer /

Brand Equity

Portfolio Stress

Testing

Cross-channel

Synergies

Recovery

Maximization

Call Center

Optimization

Contact

Strategies

Optimization

Survey Score

Analysis

Product

Positioning

Capital

Allocation

Investment

Planning

Fraud

Pattern

Recognition

Customer

Behaviour

Analysis

KPI

Measurement &

Reporting

Reactivation /

Silent

Attrition

Key Driver /

Trigger

Analysis

Model

Risk

Management

Asset

Liability

Management

Fraud

Detection /

Investigation

Framework

Customer

Lifetime Value

Retail Banking

22

Risk Management ResearchData Management &

Performance ReportingMarketing & CRM

Portfolio Stress Testing & Risk Assessment

End-to-end Market / Equity Research & Opportunity Identification

Data Aggregation and Quality Assessment

Customer Segmentation and Analysis

Fraud AnalysisFinancial Analysis of Target

Companies for M&A

Performance Analytics and

Reporting

Segment Performance and

Reporting

Optimal Asset Allocation

Strategy

Financial Analysis of

Assets and PortfolioInteractive Dashboards

Segment P&L Analysis and

Forecasting

Servicing Rights Valuation

Market and Industry

Specific Analysis and

Reporting

Reporting and Analysis

Support for End Customers

Cross-sell / Up-sell

Strategy

Cash Flow Modeling And

Forecasting

Financial and Compliance

Reporting

Driver Analysis for

Customer Satisfaction

Instrument Valuation /

Pricing

Issue Resolution

Workflows

Corporate Banking

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Investment Banking

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Trade

Services

Data

Management

Record

KeepingCorp. Actions

Risk

ManagementReconciliation Compliance Reporting

Slippage costs

Pricing data analytics

Tax reclaimsEvent monitoring

VaR modeling Failed tradesTrade surveillance

Executive reports

Security

selection

Reference

data

Managed

accounts

Unusual trade

activity

Asset class

concentrationClaims review

Exeption

managementTrade reports

Execution

quality

Market data

analytics

Cash

Management

Competitive

intelligence

Inventory

management

Cash

movement

Do Not trade

lists

Ad Hocs

reporting

Trade sizing

decisions

Trade data

analysis

Cross selling

opportunities

Risk

attribution

models

Event driven

monitoring

Performance

measurement

Value add across the entire range of services

Predictive

work

Reporting

solutionsTax mgmt. Trade support

Modal

validation

Handling big

data sets

Support

services

Cost effective

reporting

dashboards

Handling big

data setsDashboards

Architecture

setup

Cleaning

functions

Inquisitive

analyticsReporting

Text mining

solutions

Performance

measurement

Data

monetization

Scalability

solutions

Monitoring

systems

Internal fraud

monitoring

Claims

handling

Investment Banking Services

25

Pricing / Risk

ManagementMarketing

Distribution

ChannelsUnderwriting

Claims

Management

Investment

ManagementCorporate

Loss ModelingRFM Direct Response Marketing

Product Selection

Fraud Detection

Fraud Detection

Early Reinsurance Recoverable Tagging

Yield Management

Pure Premium

Models

Campaign

ReportingProductivity

Automated

Underwriting

Severity

Forecasting

Reinsurance

Optimization

Hedging

Strategies

Competitive

Market Analysis

Market

Planning

Production

Forecasting

Straight

through

processing

Claims Staffing

Optimization

Asset Liability

Matching

Price

Optimization

Management

Market Mix

ModelingGoal-Setting

Expense

Management

Productivity

Analysis

Portfolio

Optimization

Class Plan

Development

Advertising Lift

Measurement

Agency

Segmentation

Expense

Management

Customer

Lifetime Value

Performance

Measurement

Loss Cost

Driver Analysis

Customer

Satisfaction &

Experience

analytics

Claims

Customer

Satisfaction

Analysis

Insurance