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June 4 th 2015 Big Data’s Big Picture Industry Perspectives Prasad Chitta All the views expressed in this presentation are purely of Author. They do not represent any official view or product direction of the Employer or Clients author works with.
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Page 1: Big data industry-perspectivesv1.0

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June 4th 2015

Big Data’s Big PictureIndustry Perspectives

Prasad Chitta

All the views expressed in this presentation are purely of Author. They do not represent any official view or product direction of the Employer or Clients

author works with.

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Data

I n f o r m a ti o n T e c h n o l o g y

Presentation

Process

Data

Systems of Recor

ds

Systems of Engagement

Structured

Semi-structured

Unstructured

Batch/Real-time

Response time

Through put

Quality

Audit

Security

Responsive

Context sensitive

User centric

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Context setting – Big Data

Business Verticals

Core TechnologyIT Services

Cloud Computing

Big Data

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Three Perspectives

A•Business – Traditional, New

B•Core Technology Products

C• IT Services

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Business Perspective – Insurance Industry

Focus Areas for Insurance Analytics

Marketing Analysis•Customer Lead Management•Campaign Management

•Channel Profitability Analysis•Social Media Analytics

Customer Management •Customer Segmentation•Customer Churn Analysis •Lifetime Value Analytics•Cross-sell & Up Sell Analytics

Claims Management•Fraud Analytics & Models•Subrogation Models•Claims Analysis

Sample KPI and Business Drivers

• Lead conversion rate• Channel ROI or Effective ness• Market share for each channel• Customer Satisfaction Index

• Profiling of customers • Customer Attrition/Retention Rate• % of Repeat Business from customer• Customer Net worth and Life time value

• Loss due to Fraudulent claims • Loss ratios• Claims Process Cycle ratios• Claims reserves and Provisions

Underwriting / Risk Management• Risk Assessment and Evaluation• Automated Underwritings•Re Insurance Retention Analysis

• Underwriting Margins / Profit Margins• Capacity required for Underwriters• Improve the retentions and profit margins

Insurance Business Analytics for effective decision making by analysing the historic data

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Digital Engagement based (new) business

facebook, uber, airbnb, Netflix etc., Shared Economy

Customer Centric Enterprise Social by default Digital crypto currencies

@

https://www.linkedin.com/pulse/battle-customer-interface-tom-goodwin-5985813315086008320

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Three Perspectives

A•Business - Traditional, New

B•Core Technology Products

C• IT Services

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Core Technology - The data processing lifecycle

Sensing

Acquiring, Validating

Storing Transactional Update

Operational Reporting,

Dashboards

ETL, Warehousing OLAP reporting

Analytics

Archiving, Purging

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Analytical services landscape

Analytical Processing of DataOperational Reporting /

MI

OLAP / BI / ETL

Analytics

Content (Unstructured)

Structured

AnalyticsDescriptive (Uni

or bivariate)

Diagnostic or Inquisitive

Discovery

Predictive

Predictive Statistical Techniques Machine Learning

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Big Data Landscape

Ever growing landscape of companies

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Three Perspectives

A•Business - Traditional, New

B•Core Technology Products

C• IT Services

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Survey Infographics

http://www.tcs.com/big-data-study/Pages/default.a

spx

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Analytics Value Chain

Business Value - Analytics Matrix

OLAP ReportingDrill-thru

Drill-Across

Insights/Limited What-ifActionable insights

Descriptive ModelingDescribe historical event

Predictive ModelingBaseline Demand

Impact of Causal Factors

Busi

ness

Val

ue

OptimizationLinear/Non-linear

programming & Simulations

Standard ReportingSales, Inventory, Business

Performance

Data ManagementInternal, Syndicated,

Decision Support Decision Guidance Advanced analytics

Why something happened?

What will happen?

What is the best that can happen?

What happened?

Analytics

RTBI

DSS

DSS – Decision Support Systems, RTBI – Real Time Business Intelligence

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Data Scientist, Data Artist, Data Philosopher?

Knowledge of

statisticsMathematics

Story telling

Ability to influence without authority

Artistic skills

Business understanding

Operations

knowledge

Architectural

understanding

Solution develop

ment

Tools Enabler

Storage Processing

Business KPI

Optimization

Excellence

Data Scientists

The challenge

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