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

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Presentation on theme: "A Federated Approach to Big Data -- IBM Watson Explorer Presented by: Ken Holmes."— Presentation transcript:

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

2 2 “Data is the New Oil” 2 “Data is the new Oil. Data is just like crude. It’s valuable, but if unrefined it cannot really be used.” – Clive Humby, DunnHumby “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!

3 The demand for Big Data solutions is real 33 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. 5 billion global subscribers in the telco industry are demanding unique and personalized offerings that match their individual lifestyles. 2 $93 billion in total sales is missed each year because retailers don’t have the right products in stock to meet customer demand. Source: 1.Harvard, Harvard Business Review, April ,IBM Institute for Business Value, The Global CFO Study, 2010.

4 © 2013 IBM Corporation4 Polling Question 1.How much of available information does a typical organization utilize? A.6% B.12% C.24% D.48% E.60%

5 Only Of Available Data is Used Forrester Research: Can You Give The Business The Data That It Needs? by Michele Goetz, November 13, % of structured 8% of unstructured

6 Big Data Exploration bridges the gap between structured and unstructured data, cloud, on-premise and external Unstructured docs Content Mgt Systems Enterprise Systems & Content Stores ERP CRMSCM SOA, ESB, Web Service Each system has its own but different structure Lacks structure Web RSS Feed ____________ Social Media Big Data Exploration 20 % 80 % World’s Total Data: Unstructured Structured Stream, Process and analyze Big Data Federate, discover and navigate Big Data sources Virtual Integration

7 © 2013 IBM Corporation7 Polling Question 2.If “data is the new oil,” what’s the first step in exploiting it? A.Start drilling immediately B.Build a refinery C.Open a chain of gas stations D.Explore to find the richest deposits

8 Understanding Big Data is critical to success 8 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

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

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

11 Big Data is everywhere, but not integrated in a single view 11 External ContentInternal Content “I am monitoring all angles – yet I can’t connect the dots.” “I don’trust the data we’re using for important decisions” “I can’t unlock the value in my data to drive economic value to my business.” “Innovation is falling short as I am unable to see the full research picture.” “I can’t find the right answers fast enough to support my customers.” ? “I can’t get my arms around all of the data in our enterprise.” Systems of record Applications and ECM and collaboration Sensor and machine data Hadoop Analytics Web Social media Mobile data Contact Center R&DMarketing Data Scientist Security

12 Unlock the value of information when users need it most 12 Create unified view of ALL information for real-time monitoring Identify areas of information risk & ensure data compliance Analyze customer data to unlock true customer value Increase productivity & leverage past work increasing speed to market Improve customer service & reduce call times Watson Explorer Discovery & exploration Unified view of all information Information-centric applications All at big data scale Unified access and fusion across all sources Data access & integration Index structured & unstructured data—in place Support existing security Federate to external sources

13 Business and IT Drivers for Big Data Exploration © 2013 IBM Corporation Understand the organization’s critical business imperatives and potential use cases Sample Business KPIs 1.Average order value 2.Profit margin 3.Net Promoter Score 4.Lifetime customer value 5.Gross margin 6.Customer acquisition rate/cost 7.Average sales price 8.Cross sell & up sell 9.Category margin 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? 1. You must invest a little time to understand the critical business imperatives Revenue attainment Cost control Customer loyalty Productivity Compliance Competitive advantage Employee engagement 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

14 Benefits of big data exploration are felt throughout the organization—some examples © 2013 IBM Corporation14 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 Manufacturing  Supply chain visibility  Access to R&D data  Improved collaboration R&D  Reduced time looking for info  Better re-use of prior research  Increased collaboration/expert identification  Increased innovation & return on R&D investment Support  Single point of access for all info  Reduced average handle time  Improved customer satisfaction  Improved morale and retention  Increased up-sell and referral HR  Higher morale & engagement  Lower churn/turnover  Knowledge transfer from senior staff  Reduced training/on-boarding time Executive  Decisions made with better information  Reduced risk  Multiple ways to critical business issues 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

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

18 Watson Explorer Customer Example - Airbus  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 Improved customer satisfaction and lowered costs Watson Explorer Custom web applications Supplier Information Service manuals Customer profiles Lessons learned Customer call details Sales pipeline 18

19 From challenges to opportunities 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 Business outcomes Product Starting Point: Watson Explorer 19 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.

20 Need 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 Large Investment Bank Quote from the bank: “We knew there had to be a better way than monitoring all those different applications one- by-one.”

21  FREE  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 Big Data NEXT MEETUP: Real-time Analytics Developer Day on Thursday, April 17 Coming Soon: Big Data & R, Watson, Cloud, MongoDB & more!

22 Thank you


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