The document provides an agenda and overview for a briefing on using MongoDB and JasperSoft for enterprise reporting. It discusses MongoDB's data model of flexible documents, query model with rich queries and analytics functions. It then outlines use cases of JasperSoft and MongoDB together for data hubbing from various sources, real-time analytics dashboards, and examples of customers using the integrated solution.

1. JasperWorld - Briefing
Enterprise Reporting with MongoDB and
JasperSoft

2. 2
• About MongoDB
• Data Model
• Query Model
• Data Aggregation
• Tools
• Use Cases
Agenda

3. About MongoDB

4. 4
MongoDB Overview
400+ employees 1,000+ customers
Over $231 million in funding13 offices around the world

5. 5
7,000,000+
MongoDB Downloads
150,000+
Online Education Registrants
35,000+
MongoDB Management Service (MMS) Users
30,000+
MongoDB User Group Members
20,000+
MongoDB Days Attendees
Global Community

6. 6
MongoDB Use Cases
Big Data Product & Asset
Catalogs
Security &
Fraud
Internet of
Things
Database-as-a-
Service
Mobile
Apps
Customer Data
Management
Data
Hub
Social &
Collaboration
Content
Management
Intelligence Agencies
Top Investment and
Retail Banks
Top US Retailer
Top Global Shipping
Company
Top Industrial Equipment
Manufacturer
Top Media Company
Top Investment and
Retail Banks

7. Data Model

8. 8
Operational Database Landscape

9. 9
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, … }
}
}

10. 10
Document Model Benefits
• Agility and flexibility
– Data model supports business change
– Rapidly iterate to meet new requirements
• Intuitive, natural data representation
– Eliminates ORM layer
– Developers are more productive
• Reduces the need for joins, disk seeks
– Programming is more simple
– Performance delivered at scale

11. Query Model

12. 12
MongoDB is Fully Featured

13. 13
Do More With Your Data
MongoDB
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
Map Reduce
• What is the ownership pattern of colors
by geography over time? (is purple
trending up in China?)
{
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, … }
}
}

14. 14
Morphia
MEAN Stack
Java
Python
Perl
Ruby
Support for the
most popular
languages and
frameworks
Drivers & Ecosystem

15. 15
Analytics & BI Integration

16. MongoDB & JasperSoft

17. 17
Why Jaspersoft/MongoDB ?
• Decision Making – Visualise your MongoDB data
– Meaningful interpretation of what lies beneath
– Bring the MongoDB value proposition to non-technical
Decision Makers
• Direct to MongoDB
– Integration for every use case
– Native Connectors & ETL
• Utilise the power of MongoDB Aggregation
Framework
– Push down to MongoDB aggregation
– Don’t need to add another layer of complexity

18. 18
Data Hub
BEFORE AFTER

19. 19
1. Data hub, replicating and consolidating data
from operational and EDW sources, allowing for
cross-function, complete 360-degree view
reporting and visualization
2. Data store enabling RT analytics and
dashboards to be generated against live,
operational data
MongoDB for Online Big Data

20. 20
Unified data services
… Benefit
• Each application can
still save its own
data
• Data is already
aggregated for cross-
silo reporting
• One cluster and data
access layer to
manage
Equities Systems
FI Systems
Derivatives
Systems
…
Reporting
……

21. 21
Jaspersoft: The Bridge to UDS
…
Equities Systems
FI Systems
Derivatives
Systems
…
EmbeddedinApplications
……
ETL
ETL
Benefit
• Phased approach
• Data blending
• Real-Time reporting
• Embedded
• Access native
functionality
• Each application can
still save its own
data
• Data is already
aggregated for cross-
silo reporting
• manage
RDBMS
New Apps

22. 22
Customer Examples
• Ericsson – success story
complete
• Clockwork Solutions –
success story complete
• Kansys – success story in
edit
• Ogilvy & Mather
• Scala
• Triumph Learning
• Masternaut
• Sagezza
• Nexgen
• CGR
• Turkey Ministries

23. 23
For More Information
Resource Location
MongoDB Downloads mongodb.com/download
Free Online Training education.mongodb.com
Webinars and Events mongodb.com/events
White Papers mongodb.com/white-papers
Case Studies mongodb.com/customers
Presentations mongodb.com/presentations
Documentation docs.mongodb.org
Additional Info info@mongodb.com
Resource Location

25. Appendix - Data Model

26. 26
Dynamic Schema
{
policyNum: 123,
type: auto,
customerId: abc,
payment: 899,
deductible: 500,
make: Taurus,
model: Ford,
VIN: 123ABC456,
}
{
policyNum: 456,
type: life,
customerId: efg,
payment: 240,
policyValue: 125000,
start: jan, 1995
end: jan, 2015
}
{
policyNum: 789,
type: home,
customerId: hij,
payment: 650,
deductible: 1000,
floodCoverage: No,
street: “10 Maple
Lane”,
city: “Springfield”,
state: “Maryland”
}