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Enterprise Reporting with MongoDB and JasperSoft
 

Enterprise Reporting with MongoDB and JasperSoft

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Presented by Daniel Roberts, Senior Solutions Architect at MongoDB, at the recent JasperWorld event during the London leg of their current European city tour. ...

Presented by Daniel Roberts, Senior Solutions Architect at MongoDB, at the recent JasperWorld event during the London leg of their current European city tour.

About the Speaker, Daniel Roberts:
Prior to MongoDB Daniel worked at Oracle for 11 years in a number of different positions, including Oracle's middleware technologies and strategy. Prior roles include consulting, product management, business development and more recently as a solution architect for financial services. Daniel has also worked for Novell, ICL and as a freelance contractor. He has a degree in Computer Science from Nottingham Trent University in the UK.

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  • Customer Data Management (e.g., Customer Relationship Management, Biometrics, User Profile Management) <br /> Product and Asset Catalogs (e.g., eCommerce, Inventory Management) <br /> Social and Collaboration Apps: (e.g., Social Networks and Feeds, Document and Project Collaboration Tools) <br /> Mobile Apps (e.g., for Smartphones and Tablets) <br /> Content Management (e.g, Web CMS, Document Management, Digital Asset and Metadata Management) <br /> Internet of Things / Machine to Machine (e.g., mHealth, Connected Home, Smart Meters) <br /> Security and Fraud Apps (e.g., Fraud Detection, Cyberthreat Analysis) <br /> DbaaS (Cloud Database-as-a-Service) <br /> Data Hub (Aggregating Data from Multiple Sources for Operational or Analytical Purposes) <br /> Big Data (e.g., Genomics, Clickstream Analysis, Customer Sentiment Analysis) <br />
  • MongoDB aims to blend the scalability and performance of K/V stores with the rich query functionality of the RDBMS <br /> <br /> With a document model, MongoDB can provide the flexible schema demanded by modern applications, supporting structured, semi structured, unstructured and polymorphic data. Through embedding data using sub-documents and arrays, they eliminate the need for expensive JOINs, enabling simple scaling across multiple nodes. <br /> <br /> At the same time, support for powerful query operators, the aggregation framework and rich secondary indexes, users do not trade away the ability to run complex queries against data. MongoDB can do this in real time, across multi-structured data sets
  • Here we have greatly reduced the relational data model for this application to two tables. In reality no database has two tables. It is much more common to have hundreds or thousands of tables. And as a developer where do you begin when you have a complex data model?? If you’re building an app you’re really thinking about just a hand full of common things, like products, and these can be represented in a document much more easily that a complex relational model where the data is broken up in a way that doesn’t really reflect the way you think about the data or write an application.
  • Rich queries, text search, geospatial, aggregation, mapreduce are types of things you can build based on the richness of the query model.
  • In terms of reporting, A number of Business Intelligence (BI) vendors have developed connectors to integrate MongoDB as a data source with their suites, alongside traditional relational dbs. This integration provides reporting, visualizations, dash-boarding of MongoDB data
  • Mix in Real Time with All Use Case coverage – Mike B <br />

Enterprise Reporting with MongoDB and JasperSoft Enterprise Reporting with MongoDB and JasperSoft Presentation Transcript

  • JasperWorld - Briefing Enterprise Reporting with MongoDB and JasperSoft
  • 2 • About MongoDB • Data Model • Query Model • Data Aggregation • Tools • Use Cases Agenda
  • About MongoDB
  • 4 MongoDB Overview 400+ employees 1,000+ customers Over $231 million in funding13 offices around the world
  • 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 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
  • Data Model
  • 8 Operational Database Landscape
  • 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 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
  • Query Model
  • 12 MongoDB is Fully Featured
  • 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 Morphia MEAN Stack Java Python Perl Ruby Support for the most popular languages and frameworks Drivers & Ecosystem
  • 15 Analytics & BI Integration
  • MongoDB & JasperSoft
  • 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 Data Hub BEFORE AFTER
  • 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 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 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 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 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
  • Appendix - Data Model
  • 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” }