Data as a Service:How Government Agencies are Using MongoDB to Build DaaS Solutions

Senior Solutions Architect, MongoDB

Dave Ericksondavid.erickson@mongodb.com

#MongoDB

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MongoDB

The Modern Operational Database

General Purpose

Open-Source

Real-time Document Oriented

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The MongoDB Company

400+ employees 1000+ customers

Over $230 million in funding13 offices around the world

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DB-Engines.com Ranks DB Popularity

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MongoDB Partners (400+) & Integration

Software & Services

Cloud & Channel Hardware

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MongoDB Use Cases

Big Data Product & Asset Catalogs

Security & Fraud

Internet of Things

Database-as-a-Service

Mobile Apps

Customer Data Management

Single View Social & Collaboration

Content Management

Intelligence Agencies

Top Investment and Retail Banks

Top Global Shipping Company

Top Industrial Equipment Manufacturer

Top Media Company

Top Investment and Retail Banks

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Document Data Model

Relational MongoDB

{ first_name: ‘Paul’, surname: ‘Miller’, city: ‘London’, location: [45.123,47.232], cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } ]}

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Fully Featured

MongoDB{ first_name: ‘Paul’, surname: ‘Miller’, city: ‘London’, location: [45.123,47.232], cars: [ { model: ‘Bentley’, year: 1973, value: 100000, … }, { model: ‘Rolls Royce’, year: 1965, value: 330000, … } }}

Rich Queries• Find Paul’s cars• Find everybody in London with a car

built between 1970 and 1980

Geospatial• Find all of the car owners within 5km of

Trafalgar Sq.

Text Search• Find all the cars described as having

leather seats

Aggregation• Calculate the average value of Paul’s

car collection

Native Indexes• Secondary• Compound• Geospatial

• Full Text• Hash• Covering

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Designed for Durability, Performance & ScaleD

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Availab

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Performance and Scale

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MongoDB Business Value

Enabling New Apps Better Customer Experience

Lower TCOFaster Time to Mission

First a bit of History

1940’s

1960’s

“On the one hand information wants to be expensive, because it's so valuable. The right information in the right place just changes your life.

On the other hand, information wants to be free, because the cost of getting it out is getting lower and lower all the time. So you have these two fighting against each other.”

Commonly attributed as comment by Stewart Brand to Steve Wozniak at the first

Hackers Conference in 1984

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Open Data Executive Order

Government Data as a Service

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Innovation means EVOLUTION

• Applications coupled to Data Islands

• Batch Data Warehouses

• Service Oriented

– Exposing remote procedure calls via Web technologies

• Resource Oriented

– Web addressable content and data

• Data Lakes

• X - as - a – Service

THESE ARE TOOLS FOR EXECUTING MISSION!Not necessarily aligned with objectives

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• Data Centric Approach– Data as the focus and product of your business

– Data at the center of your architecture

– Decouple infrastructure from schema and format

– No Apps?, Multiple Apps?, 1 Killer App?

Data as a Service

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• Combines strengths of recent technology trends– Enterprise controls of Service Oriented– Ease of consumption Resource Oriented– Elastic Scale of Cloud / Virtual Computing– Platform Independence, Non Proprietary Data Format

• Reusable / Transferable Infrastructure enablesRepeatable Success

Data as a Service

Use Cases and Examples with MongoDB

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• VA VLER

– Data as a central service

• CFPB

– Open Data Initiatives

• FCC

– Crowd Sourced Mobile Speed Tests

• City of Chicago

– Predictive analytics improve city services

Use Cases

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• Virtual Lifetime Electronic Record

• Challenge– Growing and evolving cyber threats

– Transformation of the healthcare industry

– Increasing pressure on federal budgets

– Greater number of Veterans receiving and using Benefits

• Multidirectional data sharing– Within the VA & with other Agencies (DoD)

– Healthcare and Benefit providers

– Veterans and other beneficiaries

Veterans Affairs VLER

http://www.va.gov/vler/

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Veterans Affairs VLER

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• eCRUD Service– Efficiency, Security, Agility– Abstract data from platform– Schema Agnostic– Enable Rapid Application Development– No Server Side Coding

• Extensive Security Engineering– Best practices in use of MongoDB security features– Hardening guides– http://www.mongodb.com/lp/contact/stig-requests

Veterans Affairs VLER

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• Protect Consumers– Making data about consumer banking, credit cards,

consumer financial products available

• CFPB open data platform: qu– Written in Clojure– MongoDB backend– https://github.com/cfpb/qu

Consumer Financial Protection Bureau

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Consumer Financial Protection Bureau - HMDA

http://www.consumerfinance.gov/hmda/

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• Challenge– Government is used to releasing data by paper report.– Spectrum Sensor data is massive and complicated– Consumers want to know their mobile and wired

broadband options

• Mobile Broadband Speed Test– Crowd source data collection– Make data returned relevant to consumer

FCC - Mobile Broadband Speed Test

We can do better than this (2011)

http://www.wired.com/2011/01/verizon-or-att-iphone

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FCC - Mobile Broadband Speed Test

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City of ChicagoWindy Grid

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MongoDB DCWashington DC, October 14

http://www.mongodb.com/events/mongodb-dc-2014

#MongoDBWorld

A day of workshops, sessions, hands on tips, Commercial and Government speakers, and great ideas.

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• DaaS platform built on MongoDB– Open data for the public– Serve data to the enterprise

• MongoDB Enterprise on up to 3 nodes for HA

• Quickstart solution deployed by our consultants

• Solution & architecture documentation

• 1 day of solution review and training

• http://bit.ly/1qXcYNA

MongoDB DaaS Quickstart

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Webinar Q&A

david.erickson@mongodb.com

http://www.mongodb.com/events/mongodb-dc-2014

Thank You