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Introduction to Big Data and Big Data
Analytics
McKinsey Cash Management Forum
December 11, 2012 v. 6a © 2012 OpTier. All rights reserved.

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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!!

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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

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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

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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/

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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

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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

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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

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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

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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
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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?
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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