1. Single customer view
The drivers, challenges, lessons learned and a success story
By Andy Ross

2. Agenda
• About MongoDB
– The Company
– The Database (MongoDB)
• Single View of Customer
2

3. MongoDB
NoSQL database
3
Document
Data Model
Open-
Source
General
Purpose
{ !
name: “John Smith”,!
date: “2013-08-01”,!
address: “10 3rd St.”,!
phone: {!
!home: 1234567890,!
!mobile: 1234568138 }!
}!

4. MongoDB Overview
4
400+ employees 900+ customers
Over $231 million in funding
(More than other NoSQL vendors combined)
Offices in NY & Palo Alto and
across EMEA, and APAC

5. Leading Organizations Rely on MongoDB
5

6. Agenda
• About MongoDB
– The Company
– The Database (MongoDB)
• Single View of Customer
6

7. MongoDB.
NoSQL Document based database.
Designed to build todays applications.
• Fast to build.
• Quick to adapt.
• Easy to scale
• Lessons learned from 40 years of RDBMS.
7

8. Relational Model
EmpID Name Dept Title Manage Payband
9950 Dunham,
PlanID BenFK Plan
100 1 PPO Plus
200 2 Standard
8
Justin
500 1500 6531 C
EmpBenPlanID EmpFK PlanFK
1 9950 100
2 9950 200
BenID Benefit
1 Health
2 Dental
DeptID Department
500 Marketing
TitleID Title
1500 Product Manager

9. Document Model
EmpID Name Dept Title Manage Payband Benefits
9950 Dunham,
9
Justin
Marketing Product
Manager
6531 C
EmpBenPlanID EmpFK PlanFK
1 9950 100
2 9950 200
Health PPO Plus
Dental Standard
PlanID BenFK Plan
100 Health PPO Plus
200 Dental Standard

10. Document Model
EmpID Name Dept Title Manage Payband Benefits
9950 Dunham,
10
Justin
Marketing Product
Manager
6531 C Health PPO Plus
Dental Standard
{
_id : 9950,
employee_name: "Dunham, Justin",
department : "Marketing",
title : "Product Manager, Web",
report_up: "Neray, Graham",
pay_band: “C",
benefits : [
{ type : "Health",
plan : "PPO Plus" },
{ type : "Dental",
plan : "Standard" }
]
}

11. MongoDB - Agility
Dynamic Schemas
EmpID Name Dept Title Manager Payband Benefits
9950 Dunham,
Health PPO Plus
Dental Standard
EmpID Name Title Payband Bonus
9952 Joe White CEO E 20,000
EmpID Name Dept Title Manager Payband Shares
9531 Nearey,
11
Justin
Marketing Product
Manager
6531 C
V 1.0 V 1.1 V 2.0
Graham
Marketing Director 9952 D 5000

12. MongoDB - Usability
Drivers
Drivers for most popular
programming languages and
frameworks
Shell
Command-line shell for
interacting directly with
database
12
Java
Python
> db.collection.insert({product:“MongoDB”,
type:“Document Database”})
>
> db.collection.findOne()
{
“_id” : ObjectId(“5106c1c2fc629bfe52792e86”),
“product” : “MongoDB”
“type” : “Document Database”
}
Perl
Ruby
Haskell
JavaScript

13. “No SQL”, But Fully Featured
13
MongoDB
{ !customer_id : 1,!
!first_name : "Mark",!
!last_name : "Smith",!
!city : "San Francisco",!
!accounts : [ !{!
! !account_number : 13,!
! !branch_ID : 200,!
! !account_type : "Checking"!
!},!
!{ !account_number : 14,!
! !branch_ID : 200,!
! !account_type : "Savings"!
!} ]!
}!
Rich Queries
• Find all Mark’s accounts
• Find everybody who opened an account
last month
Geospatial • Find all customers that live within 10
miles of NYC
Text Search • Find all tweets that mention the bank
within the last 2 days
Aggregation • What’s the average value of Mark’s
accounts
Map Reduce • How many customers that have a
checking account also have an IRA

14. MongoDB - Scalability
• High Availability
• Auto Sharding
• Enterprise Monitoring
• Grid file storage
14

15. Common FS Use Cases
15
Capital Markets
1. Reference Data
Management
2. Risk Analysis &
Reporting
3. Tick Data Capture
& Analysis
4. Customer Portal
5. Portfolio and P&L
Reporting
6. Trade Repository
7. Order Capture
Banking
1. Single View of
Customer
2. Online Banking
3. Reference Data
Management
4. Risk Analysis &
Reporting
5. Product Catalog
6. Cybersecurity
Threat Analysis
Insurance
1. Single View of
the Customer
2. Online Quoting
3. Customer Portal
4. Risk Analysis &
Reporting
5. Reference Data
Distribution
6. Policy Definition
Catalog

16. Agenda
• About MongoDB
– The Company
– The Database (MongoDB)
• Single View of Customer
16

17. Single View of a Customer -
Requirements
• Extract customer info from many source systems
as often as desired
• Load into one database and application
• Link data together for each customer
• Query for all customer and associated product
info at once
• Enable CSRs, RMs/Agents, customers, etc. to
know all customer and product information at
once
17

18. How most companies approach it
ETL
Transformation & Access
Source Layer BI Abstraction &
18
Reporting Layer
Acquisition Layer
Extraction &
Staging
Cleansing
Atomic Layer
MDM
Web Services
Dashboards &
Web Reports
Ad-hoc reports &
Analytics
Corporate Data Warehouse
Data
within
range
Data Lineage and Metadata
Layer
Transformation &
Calculation
Performance &
Access
Change Data
Data not
null
!
Data in
right
format
Reject Data
Normalisation
& Storage

19. How most companies approach it
ETL
Transformation & Access
Source Layer BI Abstraction &
19
Reporting Layer
Acquisition Layer
Extraction &
Staging
Cleansing
Atomic Layer
MDM
Web Services
Dashboards &
Web Reports
Ad-hoc reports &
Analytics
Corporate Data Warehouse
Data
within
range
Data Lineage and Metadata
Layer
Transformation &
Calculation
Performance &
Access
Change Data
Data not
null
!
Data in
right
format
Reject Data
Normalisation
& Storage
New Business
Requirement

20. How most companies approach it
ETL
Transformation & Access
Source Layer BI Abstraction &
20
Reporting Layer
Acquisition Layer
Extraction &
Staging
Cleansing
Atomic Layer
MDM
Web Services
Dashboards &
Web Reports
Ad-hoc reports &
Analytics
Corporate Data Warehouse
Data
within
range
Data Lineage and Metadata
Layer
Transformation &
Calculation
Performance &
Access
Change Data
Data not
null
!
Data in
right
format
Reject Data
Normalisation
& Storage
New Business
Requirement
Understand
schema
Change &
Modify
Change &
Modify
Change &
Modify

21. Architecture with MongoDB
Source
database 1
Source
database 2
21
… Source
Database 40
Any schema to
JSON
Document
• per product
• per customer
App 1
App 2
App 3
OLTP/real-time
access

22. Single View of a Customer –
Why MongoDB?
• Dynamic schema => can handle vastly different data together and
22
can keep improving and fixing issues over time easily
• High scale/performance => directly impacts customer experience or
CSR MTTR so every second counts
• Auto-sharding => can automatically add processing power as
customers and products are added
• Rich querying => supporting ends users directly requires multiple
ways of access and key/value is not sufficient
• Aggregation framework => database-supported roll-ups for analysis
on data hub for customer information by marketing, sales, etc.
• Map-reduce capability (Native MR or Hadoop Connector) => batch
analysis looking for patterns and opportunities in data hub

23. And We’ve Done it Before
• MetLife Leapfrogs Insurance Industry with
MongoDB-Powered Big Data Application
• New York—May 7, 2013—10gen, the MongoDB company, today
23
announced that MetLife, Inc. selected MongoDB as the data engine
for “The Wall”, an innovative customer service application that went
live last month. …
• http://www.10gen.com/press/metlife-leapfrogs-insurance-industry-mongodb-powered-
big-data-application

24. Case Study: Tier 1 Global Insurance
Provider
Source
database 1
Source
database 2
24
… Source
Database 40
Custom app
exports JSON
Document
• per product
• per customer
CSR Application
Customer
Application
Agent/RM
Application
OLTP/real-time
access
Future phases

25. Customer Records in Source
Systems, e.g. banking
25
Personal Bank Accounts
• Account ID
• Open date
• First name
• Last name
• Joint First Name
• Joint Last Name
• Joint SSN
• Address
• City
• State
• Zip
• Address 2
• Home phone
• Work phone
• APR
• Account type
• Branch ID
• Region ID
• ….
Credit Cards
• CC number
• SSN 1
• Full name 1
• Address 1
• City 1
• State 1
• Zip 1
• SSN 2
• Full Name 2
• Address 2
• City 2
• State 2
• Zip 2
• Primary phone 1
• Mobile phone 2
• Issue date
• Reward type
• ….
Mortgages
• Mortgage ID
• Borrower name
• Borrower SSN
• Borrower address
• Borrower city
• Borrower state
• Borrower zip
• Co-borrower SSN
• Co-borrower name
• Co-borrower address
• Co-borrower city
• Co-borrower state
• Co-borrower Zzp
• Mobile phone
• Effective date
• Term
• Interest
• Money down
• Principal loan
• Total loan
• ….

26. Joint Bank Account Document
{
26
_id : ObjectId("4e2e3f92268cdda473b628f6"),
accountID: 9874983789,
accountType: “Checking”,
ownershipType: “Joint”
accountOwners: [
{ firstName : ”John",
lastName: “Smith”,
address: “52 Vanderbilt Ave.”, …},
{ firstName : ”Anne",
lastName: “Smith”,
address: “52 Vanderbilt Ave.”, …} ]
openDate: ISODate("2013-02-15 10:00”)
…
}
> db.accts.find( { accountOwners: {$elemMatch: {
lastName: “Smith”,
address: “52 Vanderbilt Ave.”}}} )

27. General document per customer per
account
{
27
_id : ObjectId("4e2e3f92268cdda473b628f6"),
sourceIDs: {
ABCSystemIDPart1: 8397897,
ABCSystemIDPart2: 2937430,
ABCSystemIDPart3: 932018 }
accountType: “Checking”,
accountOwners: [
{ firstName : ”John",
lastName: “Smith”,
contactMethods: [
{ type: “phone”, subtype: “mobile”, number: 8743927394},
{ type: “mail”, address: “58 3rd St.”, city: …} ]
possibleMatchCriteria: {
govtID: 2938932432, fullName: “johnsmith”, dob: … } },
{ firstName : ”Anne",
maidenName: “Collins”,
lastName: “Smith”, …} ],
openDate: ISODate("2013-02-15 10:00”),
accountFeatures { Overdraft: true, APR: 20, … }
}
OR creditCardNumber: 8392384938391293
OR mortgageID: 2374389
OR policyID: 18374923

28. Infusion.
The Way Forward
Infusion unites insight, creativity, and
technology to accelerate and transform
business for leading companies around
the world.

29. A global presence
Toronto New York Krakow
Dallas Raleigh
Houston
Boston
London
Wroclaw
Malta
Singapore

30. 40
Our people

31. A history of success with the largest customers

32. 2014 PARTNER OF THE YEAR
Application Development
Winner
TOP 5 COOLEST INSURANCE APPS
MetLife, Infinity
Winner
2014 PARTNER OF THE YEAR
Winner
2014 WINDOWS MOBILITY
PARTNER OF THE YEAR
Winner
2014 BEST DIGITAL COMMUNITY
National September 11 Memorial &
Museum
HonorableMention
2014 Awards

33. Drivers and difficulties
Single customer view is a goal that many large firms are striving to
achieve, but it has its challenges

34. Why have a Single Customer View
Source: Experian April 2012
Enhance the customer
experience
Improve operational
efficiency
Increase cross-selling
opportunities
Improved marketing and
product development
Regulatory requirement

35. It is difficult
Consequences
of M&A
Numerous
systems and
inconsistent
formats
Customer
centric versus
product centric
Weary of large
programmes
The challenge: how does a big company act like a start-up?

36. How to be successful
Lessons learned from the many single customer projects that we are
involved with

37. How to be successful?
Behave like a start-up
Strong champion
Constrain
Modern technology Sell the idea

38. How to leapfrog?
Have a vision Make it beautiful Make it real
You can do things differently!

39. The MetLife story

40. One day we got an email from Gary…
Business context
New MetLife CIO with a (30/60/90) plan
Get the company moving fast
Introduce new technology
Solve a problem that would improve the customer experience

41. Business challenge
Asked if we could help build an application that
would produce a 360° view of his new customers
using mongoDB noSQL technology
and have a Facebook style interface?
70
different systems
140yrs
customer data
45million
policies
100million
transactions
One day we got an email from Gary…

42. 2
weeks
90
days
The approach
Prototype
Delivered the application

43. The Wall unmasked

44. The benefits – improved customer experience

45. Further information
MetLife press release: http://www.metlifegto.com/news/Built-in-record-time--
the-MetL
Interview with John Bungert, Senior Architect at MetLife:
http://www.mongodb.com/customers/metlife-interview
Presentation by Jason Lombardo, AVP, Software Engineer, MetLife:
http://www.mongodb.com/presentations/business-track-metlife-leapfrogs-insurance-
industry-mongodb-powered-big-data
Lots of interviews and articles. Just Search ‘MetLife The Wall’

46. Q&A