Download as PDF, PPTX
![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" }
]
}](https://image.slidesharecdn.com/360viewofthecustomer-30sepwebinar-141001125926-phpapp01/85/Single-View-of-the-Customer-10-320.jpg)
![“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](https://image.slidesharecdn.com/360viewofthecustomer-30sepwebinar-141001125926-phpapp01/85/Single-View-of-the-Customer-13-320.jpg)
![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.”}}} )](https://image.slidesharecdn.com/360viewofthecustomer-30sepwebinar-141001125926-phpapp01/85/Single-View-of-the-Customer-26-320.jpg)
![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](https://image.slidesharecdn.com/360viewofthecustomer-30sepwebinar-141001125926-phpapp01/85/Single-View-of-the-Customer-27-320.jpg)
Uploaded byMongoDB
Single View of the Customer
The document discusses single customer view as a goal for large firms and the challenges involved. It provides an example of how MetLife was able to achieve a single customer view using MongoDB, developing a prototype customer profile application called "The Wall" in just 2 weeks that drew from 70 different systems and improved the customer experience. Lessons from successful single customer view projects emphasize behaving like a startup by having a strong champion, using modern technology, and selling the benefits of the idea.
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Single View of the Customer
- 1. Single customer view The drivers, challenges, lessons learned and a success story By Andy Ross
- 2. Agenda • AboutMongoDB – 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 Relyon MongoDB 5
- 6. Agenda • AboutMongoDB – The Company – The Database (MongoDB) • Single View of Customer 6
- 7. MongoDB. NoSQL Documentbased 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 EmpIDName 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 EmpIDName 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 EmpIDName 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”, ButFully 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 UseCases 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 • AboutMongoDB – The Company – The Database (MongoDB) • Single View of Customer 16
- 17. Single View ofa 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 companiesapproach 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 companiesapproach 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 companiesapproach 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 ofa 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 Doneit 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: Tier1 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 inSource 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 AccountDocument { 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 percustomer 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 WayForward 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.
- 31. A history ofsuccess with the largest customers
- 32. 2014 PARTNER OFTHE 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 aSingle 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 besuccessful Lessons learned from the many single customer projects that we are involved with
- 37. How to besuccessful? 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.
- 40. One day wegot 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 Askedif 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.
- 44. The benefits –improved customer experience
- 45. Further information MetLifepress 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.