www.optier.com




Introduction to Big Data and Big Data
Analytics
McKinsey Cash Management Forum

December 11, 2012            v. 6a © 2012 OpTier. All rights reserved.
www.optier.com




Agenda
• What is big data and how much data?
• What's causing this disruption and why now?
• Is it hype or real and who are the players in Big Data and
  Analytics?
• What's wrong with the current Data Intelligence process?
• What's the impact for financial services?
• Use Cases - Its all about the Analytics!

   This is a lot to accomplish in 25 mins and right after lunch!!
www.optier.com




Big Data Everywhere!
• Lots of data is been collected and warehoused…

₋   Web data and e-commerce data
₋   Transaction Data
₋   Mobile and end-user data
₋   Purchase data from stores
₋   Bank/Credit Card data
₋   Social networks
₋   Video and preference data
₋   Machine and Sensor Data
www.optier.com
www.optier.com




How Much Data?
IDC says Digital Universe will be 35 Zettabytes by 2020…..
 For reference 1 Zettabye = 1,000,000,000,000,000,000,000 bytes of data or 1 Billion Terrabytes, with 80% of that
                                   data will be from internal enterprise systems!



Facebook at 1B Users                   Enterprise Data Growth                      Mobile Payment TX’s
www.optier.com




What's causing this disruption and why now?
Big Data is the confluence of three trends consisting of Big Transaction Data, Big
Interaction Data and Big Data Processing

         1                                                                                      2
             Big Transaction Data                            Big Interaction Data
               Transaction Context                               Other Interaction Data
               •   Core Systems Transaction                      • Mobile data
               •   Customer/Channel Data         Big Data        • Video data
                                                                                 •Image /Text
                                                                                 •Clickstream
               End User Experience               Analytics       • Sensor data   •Scientific
               •   Web Analytics
               •   End-User Data                                 Social Media
               IT Performance
               •   APM data
               •   Machine or log data




                                         3 Big Data Processing
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  Who are the players in Big Data & Why

                                       WHO                                                                     WHY   (big money!)




Source: Forbes , Dave Feinleib   http://www.forbes.com/sites/davefeinleib/2012/06/19/the-big-data-landscape/
www.optier.com




Lets separate the Signal from the Noise
Make no mistake… It’s all about REVENUE…..
                                                    Sales Then              Sales Now


Companies are investing in Big Data and
Analytics looking to solve big problems
 Context for Interactions and Transactions
 User Insights and behavior patterns         Online Marketing Then    Online Marketing Now
 Operational Intelligence
 Investment Decisioning
 Cross channel interactions
 Risk and Fraud Preventions                  Then, Unhappy Customer    Now, Customer Experience

 Predictive and Visual Insights
 Impact of IT performance
www.optier.com




Issues with Incumbents
…. But it’s NOT that easy to do !!… examples often used are companies (Google, Amazon,
Apple, etc) that designed capturing context & analytics into their business transactions
and applications.. What do the rest of us do whose core revenue and client facing
applications have been built over years…?

                    Typical BI/BA Effort
                                                                                                                         •      Batch Orientated
                                                                                                                         •      Slow Response – Days not minutes
                                                                                                                         •      Cannot be reconfigured on the fly
                                                                                                                         •      Very expensive requiring multiple
                                                                                                                                tools and resources
                                                                                                                         •      Very IT intensive (80% of the cost)
                                                                                                                         •      Complex – requiring manual data
                                                                                                                                mapping, data scrubbing and
                                                                                                                                establishing context




Source: Gartner (March 2012) – Typical analytic process using CRISP-DM, the cross-industry standard process for data mining methodology
www.optier.com




The OpTier Perspective
We believe the key is establishing business context in as near real-time as possible.
Without context lots of time and money is spent inferring context and relationships before
you can even attempt to create insights….

Establishing Business Context means you have to capture in real-time:

                       WHO (the user and customer data)
                       WHAT (what were the user actions and behaviors)
                       WHERE (location and access points)
                       HOW (device type, channel, formats, TRX path)
                       WHEN (timings, frequency,
                       WHY (Unique business data)
                       SERVICE (Performance, topology, experience)
                       OUTCOME (Success/Failure, Abandon, Follow-on)

… across the entire customer interaction, and across the entire end – end business
service
www.optier.com




OpTier’s Secret Sauce
As stated, establishing context is difficult unless you have built this into your applications. Few have,
but OpTier has patented something called ACTIVE CONTECT TRACKING…

   OpTier captures context in real-time HORIZONTALLY across the end to end Business Service ……..




 ... capturing and storing ALL customer transactions with detailed business context and service measurements …

                                     Actions,                                     Unique     Outcomes
                   Customer &                        Device &     Service
                                     Paths &                                      Business   Success or
                    User Data                        Location   Performance
                                    Behaviors                                      Data      Abandons



 ... Mapping Business Outcomes, IT Performance and customer behaviors in real-time enabling …
                          Business Performance Insights          Operational Intelligence
                                                                                                 Low Cost
       Real-time
                                                                                                 Dynamic
       Immediate

         Actual                                                                                Non IT centric
www.optier.com




     Use Cases for Financial Services Business
     stakeholders?
                         Heavy focus from business and marketing users
                       Customer behavior and patterns by channels especially mobile with a
                        focus on application/user optimization and campaign insights
                       Real-time marketing campaign impacts on actual business activity and
                        business results
                       Incremental fraud prevention techniques by isolating transaction and
                        user patterns (looking at social data)
                       End customer servicing transparency capturing business activity and
                        quantifying results
                       Understanding cross-channel relationships to enable cross-sell or
                        activity impacts – lots of cost optimization for call-center ?
                       Impact of IT performance issues on customer behavior, retention and
                        business performance
                       Spend allocation based on actual cost per transactions of underlying
                        asset usage
                       Understanding high value churn (or segmenting

12
www.optier.com




 Use Cases for Financial Services IT/Operations
 stakeholders?
                     Common IT questions that BDA can answer
                      Are meeting our operational targets in delivering always-on to
                       the business and end-users?
                      What actions can reduce the most cost based on actual
                       usage?
                      My business service is made up of multiple apps, I need alerts
                       across the entire process?
                      What are my costs per transaction relative to the underlying
                       infrastructure pieces?
                      How are my top client facing applications performing and are
                       we delivering exceptional experience?
                      Am I investing in the applications and services that deliver the
                       most revenue and impact?




13
www.optier.com




Summary
•   There is lots of data and it is growing rapidly. It’s not all high quality and the main insights appear
    to be in within the enterprise (versus social etc.). Big Data may not be all about size!

•   There is a lot of hype and a lot of vendors in the Big Data and analytics space. Beware the hype! I
    suggest you make real transaction data the cornerstone. It’s the real source of the truth

•   The driving force is to find insights to drive new revenue, new clients and extract more from your
    current processes, clients and investments

•   The incumbents have a problem. It is IT centric, expensive and all the time is spent attempt to
    establish context before they even start asking questions and seeking insights

•   OpTier’s perspective is that capturing context and looking at the actual business and user
    transactions, the supporting IT performance and the eventual business outcome is the key to
    valuable insights

•   Financial services is a key industry segment and expect a rapid growth is specific use cases. There
    will be some specific FS big data companies that will provide turnkey solutions

McKinsey Big Data Overview

  • 1.
    www.optier.com Introduction to BigData and Big Data Analytics McKinsey Cash Management Forum December 11, 2012 v. 6a © 2012 OpTier. All rights reserved.
  • 2.
    www.optier.com Agenda • What isbig data and how much data? • What's causing this disruption and why now? • Is it hype or real and who are the players in Big Data and Analytics? • What's wrong with the current Data Intelligence process? • What's the impact for financial services? • Use Cases - Its all about the Analytics! This is a lot to accomplish in 25 mins and right after lunch!!
  • 3.
    www.optier.com Big Data Everywhere! •Lots of data is been collected and warehoused… ₋ Web data and e-commerce data ₋ Transaction Data ₋ Mobile and end-user data ₋ Purchase data from stores ₋ Bank/Credit Card data ₋ Social networks ₋ Video and preference data ₋ Machine and Sensor Data
  • 4.
  • 5.
    www.optier.com How Much Data? IDCsays Digital Universe will be 35 Zettabytes by 2020….. For reference 1 Zettabye = 1,000,000,000,000,000,000,000 bytes of data or 1 Billion Terrabytes, with 80% of that data will be from internal enterprise systems! Facebook at 1B Users Enterprise Data Growth Mobile Payment TX’s
  • 6.
    www.optier.com What's causing thisdisruption and why now? Big Data is the confluence of three trends consisting of Big Transaction Data, Big Interaction Data and Big Data Processing 1 2 Big Transaction Data Big Interaction Data Transaction Context Other Interaction Data • Core Systems Transaction • Mobile data • Customer/Channel Data Big Data • Video data •Image /Text •Clickstream End User Experience Analytics • Sensor data •Scientific • Web Analytics • End-User Data Social Media IT Performance • APM data • Machine or log data 3 Big Data Processing
  • 7.
    www.optier.com Whoare the players in Big Data & Why WHO WHY (big money!) Source: Forbes , Dave Feinleib http://www.forbes.com/sites/davefeinleib/2012/06/19/the-big-data-landscape/
  • 8.
    www.optier.com Lets separate theSignal from the Noise Make no mistake… It’s all about REVENUE….. Sales Then Sales Now Companies are investing in Big Data and Analytics looking to solve big problems  Context for Interactions and Transactions  User Insights and behavior patterns Online Marketing Then Online Marketing Now  Operational Intelligence  Investment Decisioning  Cross channel interactions  Risk and Fraud Preventions Then, Unhappy Customer Now, Customer Experience  Predictive and Visual Insights  Impact of IT performance
  • 9.
    www.optier.com Issues with Incumbents ….But it’s NOT that easy to do !!… examples often used are companies (Google, Amazon, Apple, etc) that designed capturing context & analytics into their business transactions and applications.. What do the rest of us do whose core revenue and client facing applications have been built over years…? Typical BI/BA Effort • Batch Orientated • Slow Response – Days not minutes • Cannot be reconfigured on the fly • Very expensive requiring multiple tools and resources • Very IT intensive (80% of the cost) • Complex – requiring manual data mapping, data scrubbing and establishing context Source: Gartner (March 2012) – Typical analytic process using CRISP-DM, the cross-industry standard process for data mining methodology
  • 10.
    www.optier.com The OpTier Perspective Webelieve the key is establishing business context in as near real-time as possible. Without context lots of time and money is spent inferring context and relationships before you can even attempt to create insights…. Establishing Business Context means you have to capture in real-time:  WHO (the user and customer data)  WHAT (what were the user actions and behaviors)  WHERE (location and access points)  HOW (device type, channel, formats, TRX path)  WHEN (timings, frequency,  WHY (Unique business data)  SERVICE (Performance, topology, experience)  OUTCOME (Success/Failure, Abandon, Follow-on) … across the entire customer interaction, and across the entire end – end business service
  • 11.
    www.optier.com OpTier’s Secret Sauce Asstated, establishing context is difficult unless you have built this into your applications. Few have, but OpTier has patented something called ACTIVE CONTECT TRACKING… OpTier captures context in real-time HORIZONTALLY across the end to end Business Service …….. ... capturing and storing ALL customer transactions with detailed business context and service measurements … Actions, Unique Outcomes Customer & Device & Service Paths & Business Success or User Data Location Performance Behaviors Data Abandons ... Mapping Business Outcomes, IT Performance and customer behaviors in real-time enabling … Business Performance Insights Operational Intelligence Low Cost Real-time Dynamic Immediate Actual Non IT centric
  • 12.
    www.optier.com Use Cases for Financial Services Business stakeholders? Heavy focus from business and marketing users  Customer behavior and patterns by channels especially mobile with a focus on application/user optimization and campaign insights  Real-time marketing campaign impacts on actual business activity and business results  Incremental fraud prevention techniques by isolating transaction and user patterns (looking at social data)  End customer servicing transparency capturing business activity and quantifying results  Understanding cross-channel relationships to enable cross-sell or activity impacts – lots of cost optimization for call-center ?  Impact of IT performance issues on customer behavior, retention and business performance  Spend allocation based on actual cost per transactions of underlying asset usage  Understanding high value churn (or segmenting 12
  • 13.
    www.optier.com Use Casesfor Financial Services IT/Operations stakeholders? Common IT questions that BDA can answer  Are meeting our operational targets in delivering always-on to the business and end-users?  What actions can reduce the most cost based on actual usage?  My business service is made up of multiple apps, I need alerts across the entire process?  What are my costs per transaction relative to the underlying infrastructure pieces?  How are my top client facing applications performing and are we delivering exceptional experience?  Am I investing in the applications and services that deliver the most revenue and impact? 13
  • 14.
    www.optier.com Summary • There is lots of data and it is growing rapidly. It’s not all high quality and the main insights appear to be in within the enterprise (versus social etc.). Big Data may not be all about size! • There is a lot of hype and a lot of vendors in the Big Data and analytics space. Beware the hype! I suggest you make real transaction data the cornerstone. It’s the real source of the truth • The driving force is to find insights to drive new revenue, new clients and extract more from your current processes, clients and investments • The incumbents have a problem. It is IT centric, expensive and all the time is spent attempt to establish context before they even start asking questions and seeking insights • OpTier’s perspective is that capturing context and looking at the actual business and user transactions, the supporting IT performance and the eventual business outcome is the key to valuable insights • Financial services is a key industry segment and expect a rapid growth is specific use cases. There will be some specific FS big data companies that will provide turnkey solutions

Editor's Notes

  • #2 Insert the date, version number and copyright line on the cover page only.