big data - key enablers, drivers & challenges

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1 When Execution Matters (Confidential) Big Data – Let’s Embrace It! By Shilpi Sharma Nov, 2012

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Page 1: Big data - Key Enablers, Drivers & Challenges

1When Execution Matters(Confidential)

Big Data – Let’s Embrace It!

By Shilpi Sharma

Nov, 2012

Page 2: Big data - Key Enablers, Drivers & Challenges

2When Execution Matters(Confidential)

Topics Covered

V3 and Enablers

3Ts and Challenges

Use Case: Sales Enablement

Page 3: Big data - Key Enablers, Drivers & Challenges

3When Execution Matters(Confidential)

Big Data Characteristics – V3

As of 2012, about 2.5 exabytes of data are created each day, and that number is doubling every 40 months or so.

More data cross the internet every second than were stored in the entire internet just 20 years ago.

30Bn pieces of content shared on Facebook every month

A petabyte is one quadrillion bytes, or the equivalent of about 20 million filing cabinets’ worth of text.

An exabyte is 1,000 times that amount, or one billion gigabytes.

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4When Execution Matters(Confidential)

What is Big Data?

Page 5: Big data - Key Enablers, Drivers & Challenges

5When Execution Matters(Confidential)

Key Enablers

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Key Enabler – Data Storage

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Key Enabler – Computation Capacity

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Key Enabler – Data Availability

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Key Drivers – Internet of Things & Big Data

18% of 2B electricity utility meters are smart meters

50B+Intelligent machines fighting for bandwidth by 2020

Page 10: Big data - Key Enablers, Drivers & Challenges

10When Execution Matters(Confidential)

Gartner Emerging Technologies Hype Cycle 2012

Investments in Big Data Infrastructure (2009-2011)

$5B+

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Industry SectorsRich in Big Data

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12When Execution Matters(Confidential)

Value Potential Across Sectors

For Hi-Tech Companies, Big Data is generated from Value Chain

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Readiness Across Sectors

Information is the only industry that will get most value from Big Data with ease.

Page 14: Big data - Key Enablers, Drivers & Challenges

14When Execution Matters(Confidential)

Big Data – 3TsTechnologies, Techniques & Talent

Page 15: Big data - Key Enablers, Drivers & Challenges

15When Execution Matters(Confidential)

Big Data Technologies

Where processing is hosted?Distributed Servers/Cloud (e.g. Amazon EC2)

Where data is stored?Distributed Storage (e.g. Hadoop DFS)

What is programming model?Distributed Processing (e.g. MapReduce)

How data is stored& indexed?High-performance schema-free database (e.g. Cassandra)

What operations are performed?Data Analytics, Semantic Processing (e.g. R)

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16When Execution Matters(Confidential)

Big Data TechniquesA set of techniques to extract patterns from large datasets by combining methods from statistics and machine learning with database management. Few examples:

Supervised Learning – Support Vector Machine Unsupervised learning – Cluster Analysis Data fusion – Signal processing, Natural Language

Processing Optimization – Genetic Algorithm, Neural Networks Predictive Modeling – Regression, Time Series Analysis

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Big Data Talent

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18When Execution Matters(Confidential)

Big Data Value Chain

Smart Sampling of Data

Finding similar items

Building Models and incremental updating of models

Aggregate

Data

Analyze

Data

Consume

DataDerive Value

Data Integration (from multiple sources)

Data harmonization (multi-rate, noisy, missing)

Data Classification

Visualization Connect the dots (Actionable Insights)

Change Management

Data Policy & Governance

Technology Management

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19When Execution Matters(Confidential)

Big Data – Management Challenges

Decision Making

Shortage of Skills

Change Management

Big data brings the potential for transformation, not the actual transformation

Clash of Technologies

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20When Execution Matters(Confidential)

Food for Thought

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21When Execution Matters(Confidential)

Take an example – A Client MeetingTypes of Data:

Internal Information: Company, Presentations, collateral, pricing, contracts

Personal Information: Territory assignment, Goal Attainment, Past interactions with customer

External Information: Company, People, Competition, Market

Data Sources:Suddenly you are going from a few office documents to hundreds of files and channels that are being continually updated.

Static like a webpage, personal profile, competitive cheat sheet

Dynamic like a YouTube channel demonstrating a competitor’s product, a blog reviewing an announcement, or twitter channel

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22When Execution Matters(Confidential)

Some Facts $135,262 – Average support costs per year for each

salesperson

7 hours/week - Average salesperson spends looking for relevant information to prepare for sales calls

50% of the information is pushed through email; only 10% is made available in a useful format

Source: Forrester Research & IDC Sales Advisory Service

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Big Data Application

Connect the dots across internal and external data for sales professional What has been sold at client? How it has been working? Where the industry is moving? What are top challenges for

the decision makers? How does it connect to product portfolio you are selling?

What has been the buying pattern at client? Any new insights based on Install Base?

Win More Deals, Increase Productivity, Sell Smarter

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24When Execution Matters(Confidential)