1. A Federated Approach to Big Data -- IBM Watson Explorer
Presented by: Ken Holmes

2. “Data is the New Oil” Exploration can be a critical step!
Data is just like crude. It’s valuable, but if unrefined it cannot really be used.”
– Clive Humby, DunnHumby
“Data is the New Oil”
“We have an economy based on a resource that is not only renewable, but self-generating. Running out is not a problem, drowning in it is.”
– John Naisbitt
Exploration can be a critical step!
Oil which is the fuel for modern economy for centuries. However, Oil in its raw form has little value. It needs to be refined and separated into a large number of consumer products, from petrol and kerosene to asphalt and chemical reagents used to make plastics and pharmaceuticals. It is also used in manufacturing a wide variety of materials.
Big Data is just like oil, in it’s raw form it provide no value to enterprise, until it is processed and valuable and actionable business insights are “distilled”.
Just like the technology that made available 100 years ago to discover oil and process it to consumable products. Big Data technology is going to transform and revolutionize the way enterprise get and use data. But before you can extract oil, you have to find out where the most productive resources are! The same applies to creating insights from data. 2 2 2

3. The demand for Big Data solutions is real
The healthcare industry loses $250 - $300 billion on healthcare fraud, per year. In the US alone this is a $650 million per day problem.1
One rogue trader at a leading global financial services firm created $2 billion worth of losses, almost bankrupting the company.
Here are some examples of how information can work to you advantage or work or against you. While these challenges pose threats, they also pose opportunities.
The healthcare industry spends roughly $250 billion on fraud, per year. By 2016, this could grow to more than $400 billion a year.
But … Insurance companies that reduce fraud will gain advantages over their competitors.
One rogue trader at a leading global financial services firm created $2 billion worth of losses, almost bankrupting the company.
But … Financial services firms can use information and analytics to detect and curb rogue trading and gain advantage over firms that don’t leverage their information.
$93 billion in total sales is missed each year because retailers don’t have the right products in stock to meet customer demand.
But … Retailers who can leverage the many sources of data available to them can optimize inventory and gain competitive advantage over companies that don’t do it as well by having the right merchandise on the shelves at the right time.
6 billion global subscribers in the telco industry are demanding unique and personalized offerings that match their individual lifestyles.
But … Telcos that can anticipate and personalize service, leading to better customer retention and average revenue per customer, will have a distinct advantage.
So while the amount of data that your organization needs to deal with presents challenges, it also presents many opportunities … these are just a few examples.
$93 billion in total sales is missed each year because retailers don’t have the right products in stock to meet customer demand.
5 billion global subscribers in the telco industry are demanding unique and personalized offerings that match their individual lifestyles.2
Source: 1.Harvard, Harvard Business Review, April 2010.
2,IBM Institute for Business Value, The Global CFO Study, 2010. 3 3 3

4. Polling Question
How much of available information does a typical organization utilize? 6%
12%
24%
48%
60%
Answer: B, according to Forrester Research
© 2013 IBM Corporation

5. Of Available Data is Used
12%
Only
If we accept that data is the new oil, then how organizations use their data can determine the winners and losers. Here’s a startling statistic: According to Forrester Research, on average organizations only use about 12% of their data! When you look at different types of data, utilization rates of structured data is only 32%. That sounds low until you consider unstructured data, which is most of the data in the world. For unstructured data, the utilization plummets to single digits -- 8%. Combined, only about 12% of data available is used. Your customers should question what data they store and what data they actually use. Clearly there is a pressing need to understand what data we have in our organizations and to understand how to utilize it.
Of Available Data is Used
32% of structured
8% of unstructured
Forrester Research: Can You Give The Business The Data That It Needs?
by Michele Goetz, November 13, 2013

6. Big Data Exploration bridges the gap between structured and unstructured data, cloud, on-premise and external
Big Data Exploration
Stream, Process and analyze Big Data
Federate, discover and navigate Big Data sources
Virtual Integration
Enterprise Systems & Content Stores
Here’s a key point about big data exploration: you need the ability to bridge both the structured and unstructured information in your organization. For years we’ve seen businesses focus on primarily structured data. However, over 80% of data in the world today is unstructured and does not live in databases. In many cases, meaningful analysis of data in your organization can only be done when pulling together data from all available sources. This is challenging, however, as organizations have many silos where all their data lives, including the cloud, which do not integrate well with each other. IBM has a solution here in the form of Data Explorer.
Lacks structure
Each system has its own but different structure
ERP
CRM
SCM
SOA, ESB,
Web Service
Content Mgt Systems
Web RSS Feed ____________
Social Media
Unstructured docs
80%
20%
World’s Total Data:
Unstructured
Structured

7. Polling Question
2. If “data is the new oil,” what’s the first step in exploiting it?
Start drilling immediately
Build a refinery
Open a chain of gas stations
Explore to find the richest deposits
Answer: D
© 2013 IBM Corporation

8. Understanding Big Data is critical to success
Explore
Discover and navigate all Big Data repositories – internal and external sources
Analyze
Analyze and compare trillions of data records from structured and unstructured sources
Understand
Correlate & combine all data sources to unearth unique relationships
Getting Started is Crucial 8

9. Big Data Analytics Watson Explorer
Phase 1: Leverage Information In-Place
Phase 2: Automate and Expand w/ Big Data Analytics
Data Scientist / Analyst
Business End User
Discover & Navigate
Advanced Analytics
Big Data Analytics
Watson Explorer
Identify Analysis-
Ready Data
Serve up Analytical Insights in Context
The Virtuous Circle of Information Analysis
Hadoop System
Stream Computing
Internal & External
Structured & Unstructured
Data Warehouse
Critical Information 9

10. Big Data Exploration helps to leverage ALL the data
TRADITIONAL APPROACH
BIG DATA APPROACH
Analyze all data
Analyzed information
Analyzed information
All available
information
Analyze small subsets of data
© 2013 IBM Corporation

11. Big Data is everywhere, but not integrated in a single view
Hadoop
Sensor and machine data
Analytics
and collaboration ?
Web
Applications and ECM
Social media
Systems of record
Internal Content
External Content
Mobile data
Contact Center
Data Scientist
All large organizations face this challenge: information is stored in may different systems and silos, but is not easily accessible at “the point of impact,” to the people who need it most. The information that people need to do their day-to-day work and make important decisions ranges from external content such as social media, feeds from mobile devices, Twitter, etc., to enterprise applications such as CRM, data warehouses, ERP, ECM and more.
Despite being surrounded by data, employees struggle to leverage the information they need at the point of impact. Regardless of role, we typically need information from multiple different sources to address their day-to-day challenges.
customer service professionals have to open several applications on their desktop at once and struggle to find the information they need to help customers or to upsell or cross-sell. This distracts from their ability to engage customers and address their issues efficiently.
Researchers may have difficulty finding out who else is working on a particular topic, or finding the results of other studies that have been done in the past.
Marketing professionals have difficulty finding and unlocking customer data to gain insights and understand the market.
The organization may be exposed to risk because there is personal information, s and other sensitive content stored where it shouldn’t be.
And corporate security officers have difficulty “connecting the dots” because they can only see information in one repository at a time.
R&D
Marketing
Security
“I can’t find the right answers fast enough to support my customers.”
“I am monitoring all angles – yet I can’t connect the dots.”
“Innovation is falling short as I am unable to see the full research picture.”
“I can’t unlock the value in my data to drive economic value to my business.”
“I can’t get my arms around all of the data in our enterprise.”
“I don’trust the data we’re using for important decisions” 11 11

12. Unlock the value of information when users need it most
Watson Explorer
Data access & integration
Index structured & unstructured data—in place
Support existing security
Federate to external sources
Discovery & exploration
Unified view of all information
Information-centric applications
All at big data scale
Unified access and fusion across all sources
We address these challenges by adding a layer of capabilities that deliver information from many different sources in a form that is useable at the point of impact.
Data Explorer provides indexing and integration capabilities across all of your data sources—both structured and unstructured—in place. So you don’t need to move data to make it accessible.
Supports the existing security model of each repository so users can’t see information that would not be accessible to them if they were directly logged into the target systems.
For external systems such as premium web-based information sources, or systems you do not choose to index directly, you can establish federated access to query the target systems and integrate results at query time. You can leverage IBM’s IIG capabilities such as MDM, as well as systems such as Business Glossary for standard taxonomies.
The resulting rich discovery and navigation capabilities provide easy access to your information with features such as dynamic categorization, rich end-user applications that deliver information in context to users based on their role and current activities. And it does all of this at the scale needed for the challenges of big data.
The result, at the point of impact,
Customer service agents can view information from multiple sources in a single view, enabling them to assist customers more efficiently.
Researchers can quickly see what’s being worked on elsewhere in the enterprise, and leverage past projects and current expertise much more easily.
Customer data is much more accessible and can be analyzed to expose new revenue opportunities.
Risk is reduced because otherwise hidden information is exposed; compliance is improved with better access to information. Security is enhanced by enabling corporate security officers and investigators to view information across multiple sources.
Clearly the ability to bring all of this information together seamlessly drives significant value in an organization.
Create unified view of ALL information for real-time monitoring
Improve customer service & reduce call times
Increase productivity & leverage past work increasing speed to market
Analyze customer data to unlock true customer value
Identify areas of information risk & ensure data compliance 12 12

13. Business and IT Drivers for Big Data Exploration
1. You must invest a little time to understand the critical business imperatives
Sample Business KPIs
Average order value
Profit margin
Net Promoter Score
Lifetime customer value
Gross margin
Customer acquisition rate/cost
Average sales price
Cross sell & up sell
Category margin
• Revenue attainment
• Cost control
• Customer loyalty
• Productivity
• Compliance
• Competitive advantage
• Employee engagement
Understand the organization’s critical business imperatives and potential use cases
2. Understand Benefits of Big Data Exploration – Do you have a way to explore important data sources? Do you have a way to deliver big data & analytics to the employees who need it?
Explore all data to determine what is relevant to big data initiatives
Enterprise systems
External data
“New” data (sensor, etc.).
Reduce cost of big data integration
Create integrated views for new insights
Reduce time-to-value
Better use/re-use of info
Deploy apps to deliver data & analytics
Improve customer service
Increase productivity
Improve employee performance
© 2013 IBM Corporation

14. Benefits of big data exploration are felt throughout the organization—some examples
Sales
Less time looking for info; more time in front of customers
360 view of customer
Faster response to new opportunities
Better up-sell/cross-sell
R&D
Reduced time looking for info
Better re-use of prior research
Increased collaboration/expert identification
Increased innovation & return on R&D investment
Manufacturing
Supply chain visibility
Access to R&D data
Improved collaboration HR
Higher morale & engagement
Lower churn/turnover
Knowledge transfer from senior staff
Reduced training/on-boarding time
Big Data Exploration use case offers multiple value propositions depending on
Where the client is in big data journey
What business issues are top-of-mind
Support
Single point of access for all info
Reduced average handle time
Improved customer satisfaction
Improved morale and retention
Increased up-sell and referral
Executive
Decisions made with better information
Reduced risk
Multiple ways to critical business issues
© 2013 IBM Corporation

15. Examples
© 2013 IBM Corporation

16. Watson Explorer for Enterprise Reporting – 360 Degree View
For many years, this automotive industry leader led the way in understanding their customer loyalty and profitability using traditional reporting tools. Their challenge has been in analyzing unstructured data in context with their traditional BI tools and empowering ALL their business users to “see the whole picture.”
Their requirements:
Discover insights into unstructured text
Scalable Platform
Secure
Rich connectivity
The Challenge
Watson Explorer Capabilities:
Connectivity framework
Powerful Text Analytics
Security model
Application Builder
In 2 weeks, Watson Explorer connected to Netezza, OBIEE, Fileshares, SharePoint to:
Aggregate Contextual Data
Increase information access
Increased Visibility into high value data
This project is expected to net a cost savings of $7m in their call center operations alone within 2 years.
The Solution
“We never thought we would be able to see ALL of our data in one place, and it took two days”

17. Watson Explorer Customer Example – Leading Analyst Firm
Adapted relevance lead to greater user satisfaction, click through and up-sell
Profile-based suggestions
Reports, analysts, and other types of contents are searchable
Rich navigation through faceting, clustering & related content
Use Watson Explorer as an “application development platform”
Integrate different content types

18. Watson Explorer Customer Example - Airbus
Improved customer satisfaction and lowered costs
Custom web applications
Problem
Provide uniform information access platform to develop multiple customer centric applications for Support, Service and Self-service
Information locked into multiple data sources with different security schemas
Solution
Provided connectivity to complex repositories such as Aqualogic, SAP R3 and KM, Siebel
Extract and index all metadata
Supported existing security policy
Run-in parallel parsing agents
Results
Indexed 2PB of data
Deployed in 1 month
Multiple front-end applications leveraging common back-end infrastructure
Single point access to all repositories
Watson Explorer
Supplier Information
Service manuals
Customer profiles
Lessons learned
Customer call details
Sales pipeline 18

19. From challenges to opportunities
Leading Medical Equipment Supplier
A leading medical device manufacturer delivers detailed knowledge about customers and products to their contact center agents to enable better engagement and asking “one more question” to increase cross-selling.
This leading medical device manufacturer found itself needing to cut costs, improve customer service and increase revenue from existing customers.
With a 360º view of each customer, and information quickly available that will resolve the customer’s issue, inbound customer calls can often quickly move beyond the immediate question being asked by the customer to engaging the customer on their next potential purchase. The contact center agent is equipped with right next action and maximize the value of that interaction at point of impact. Knowing everything about that client, combined with the agent’s assessment of their mood on that particular call is critical. If the client's account is in arrears, they might want to remind them of that rather than try to sell them something else. If a client has Product A but not Product B, they might want to explain how Prod B could help them get more value out of Prod A. Or maybe there is a new offering or a webcast you want them to know about. All of this is enabled by the 360º view..
Challenges
Drive cost savings in the call center and improve customer satisfaction
More efficient use/re-use of information
Cope with layoffs forced by increased taxes and financial downturn
Outcome
Improved productivity of call center reps and other employees
Increased services revenue by creating opportunity to ask “1 more question”
Improved contact center efficiency, enabling support of larger revenue base without adding headcount
Promoted self-service & knowledge management throughout organization
Technology cost savings through retiring old systems or moving them to the background
Business outcomes
Increased revenue and decreased cost in the call center
Increased customer satisfaction & employee engagement
Created opportunities from each customer interaction - “one more question,” targeted to individual client situation
Product Starting Point: Watson Explorer 19 19

20. Large Investment Bank Need Solution/Status Quote from the bank:
Reduce risk and improve compliance
Too many silos to monitor across multiple LOBs—needed visibility to all from a single point
Improve knowledge sharing and research
Deliver 360º view of customers, products and assets
Solution/Status
Suite of IBM products provided solution that no other single vendor could match
Watson Explorer deployed in:
PoC in Consumer Client Banking
Risk and compliance solution
Asset management group PoC
Call center knowledge management
Big data initiative
Quote from the bank:
“We knew there had to be a better way than monitoring all those different applications one-by-one.” 20

21. Big Data Developers @ meetup.com/BigDataDevelopers FREE 1000+ Members
All types of practitioners
All skill levels
San Jose & Foster City
Evenings, Full Day, & Afternoons
Hands-on Labs
Live Streaming
Past Meetups:
Hadoop
Text Analytics
Real-time Analytics
SQL for Hadoop
HBase
Social Media Analytics
Machine Data Analytics
Security and Privacy
meetup.com/BigDataDevelopers
NEXT MEETUP: Real-time Analytics Developer Day on Thursday, April 17
Coming Soon: Big Data & R, Watson, Cloud, MongoDB & more!

22. Thank you
THANK YOU