Partner Webinar: Deliver Big Data Apps Faster With Informatica & MongoDB
 

Partner Webinar: Deliver Big Data Apps Faster With Informatica & MongoDB

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Informatica + MongoDB is a powerful combination that increases developer productivity up to 5x, enabling them to build and deploy big data applications much faster. Informatica provides access to ...

Informatica + MongoDB is a powerful combination that increases developer productivity up to 5x, enabling them to build and deploy big data applications much faster. Informatica provides access to virtually all types of data from modern and legacy systems at any latency, processes and integrates data at scale, and delivers it directly into MongoDB.

With Informatica, companies can unlock the data in MongoDB for downstream analytics to improve decision making and business operations. Using the Informatica PowerCenter Big Data Edition with the PowerExchange for MongoDB adapter users can read and write data in MongoDB, parse the JSON-based documents and then transform the data and combine it with other information for big data analytics - all without having to write a single line of code.

In this webinar you will see a live demo and learn how to:
- Discover insights from Big Data faster
- Run better applications with better data
- Lower costs of data integration
- Deliver business impact with rapid deployment

See the full presentation at:

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  • And of course what we are seeing is not new. We have seen this phenomenonbefore as wave after wave of technology introductions came upon us, each bringing its own set of opportunities to deliver on bigger and better business outcomes. As has been clear over the past 10-15 years though, the pace is increasing. Just consider that Facebook, Twitter, iPhones weren’t there a mere decade ago. Each wave brings new technologies– new applications, new computing platforms, new development languages. And of course, it is not just the new that IT needs to deal with though when we think of the disruptions. Almost every technology on this slide is still around in your data centers – mainframes, SAP ERP, Oracle databases, plus we have to bring in the new such as Hadoop, VMWare, cloud services like Amazon Web Services.In addition to the technologies, one pervasive theme is the explosion in data collected and required across all of these different waves. This is not just the volume but in the sheer number of connection points between the different information sources. In many ways, the information is the most important aspect in today’s world and the technologies becoming the medium whereby we collect or disseminate insights or insight driven interactions.
  • We live in a world that’s dominated by smart devices that are constantly connected to each other and the internet – where data is collected about more events or things than ever before and where the promise of how data can change the way the world operates in every aspect – how we run and operate companies, how we build new customer experiences, or build new products. We are in the process of building out a very big data-centric world!This new world impacts every industry and every domain – from aviation where companies like GE now embeds sensors into aircraft engines that can evaluate the engine performance constantly – allowing them to increase fuel efficiency of these engines and optimize engine maintenance. Or in healthcare where genome sequencing is going to reach the mainstream level in the next couple of years, allowing individuals to get it done at a local Walgreens. Imagine the impact on personalized healthcare and treatment for diseases or things like obesity.Business is connecting innovation to big data. Here are some common use-cases across industries:Financial ServicesRisk & Portfolio Analysis,Investment RecommendationsRetail & TelcoProactive Customer Engagement,Location Based ServicesMedia & EntertainmentOnline & In-Game BehaviorCustomer X/Up-SellManufacturingConnected Vehicle,Predictive MaintenanceHealthcare & PharmaPredicting Patient Outcomes,Total Cost of CareDrug DiscoveryPublic SectorHealth Insurance Exchanges,Public Safety,Tax OptimizationFraud Detection
  • Move policies into MongoDB – this is basically taking massive amounts of policy information from a dozen relational data sources, transforming from relational to hierarchical JSON documents and populating MongoDB.
  • Once data is in prod then take MongoDB data, transform it and put it into a data warehouse. This is mostly new or changed data.
  • High Productivity Development EnvironmentProvides a visual metadata-driven development environment so developers can achieve up to 5 times productivity over hand-coding data integration from scratch.Universal Data AccessProvides access to virtually all types of data including RDBMS, mainframe, ERP, CRM, social media, machine and sensor device data, Cloud applications, and industry standards data (e.g. FIX, SWIFT, HL7, HIPAA, ASN.1, EDI, etc.)High-Speed Data Ingestion and ExtractionAccesses, loads, transforms, and extracts big data between source and target systems and MongoDB at high speeds using high-performance connectivityMetadata Discovery for Flexible Data ModelsAutomatically discovers schemas by sampling records in a collection to provide a representative collection schema. Users can edit the discovered schema by adding or removing columns required for analysis.Embedded Entity AccessCreates pivoted columns so users can easily access data from Embedded Documents and Arrays and integrate data independent of the application data modeling in MongoDBJSON Document HandlingInteracts with MongoDB’s BSON serialization format with the ability to ingest complex JSON structures directly into MongoDB as documents or extract selected JSON elements for analysis.Distributed Data Access through Read PreferencesProvides "Read Preferences" that allows users to choose which members of the MongoDB Replica Set to use for data integration. This gives users a choice to distribute data integration jobs to secondary nodes in a replica set, so as to not affect performance of the primary node and the main application load.Map Once, Deploy AnywhereIncludes the Vibe Virtual Data Machine so users can build data integration pipelines once and deploy them anywhere such as distributed grid computing platforms like Hadoop, on-premise, or in the CloudUnified Administration and High AvailabilityAutomatically schedule and coordinate data integration workflows with high availability and reliability using a unified administration console
  • Metadata Discovery for Flexible Data ModelsAutomatically discovers schemas by sampling records in a collection to provide a representative collection schema. Users can edit the discovered schema by adding or removing columns required for analysis.
  • Embedded Entity AccessCreates pivoted columns so users can easily access data from Embedded Documents and Arrays and integrate data independent of the application data modeling in MongoDB
  • JSON Document HandlingInteracts with MongoDB’s BSON serialization format with the ability to ingest complex JSON structures directly into MongoDB as documents or extract selected JSON elements for analysis.
  • Distributed Data Access through Read PreferencesProvides "Read Preferences" that allows users to choose which members of the MongoDB Replica Set to use for data integration. This gives users a choice to distribute data integration jobs to secondary nodes in a replica set, so as to not affect performance of the primary node and the main application load.
  • Vibe is the industry’s first and only embeddable virtual data machine to access, aggregate and manage data – regardless of data type, source, volume, compute platform or user. It lets you map once, and deploy anywhere. So you can take your logic that may have defined on-premise, then move it to the cloud. And then move it to Hadoop, or embed it in an application– without recoding.This makes your architecture faster, more flexible, and futureproof.Business BenefitFive time faster turn-around from business idea to solutionAdapt the technology to your business, not vice-versaUtilize all your data, regardless of location, type or volumeIT BenefitFive times faster project deliveryEliminate skills gaps for adopting new technologies and approachesReduce cost of maintaining complex assortment of technologies
  • Unified Administration and High AvailabilityAutomatically schedule and coordinate data integration workflows with high availability and reliability using a unified administration console
  • Discover Insights from Big Data FasterThe power of big data means you can access and analyze all of your data. A growing number of the worlds’ top companies and government agencies use MongoDB for applications today which means more and more data is being stored in MongoDB. Using Informatica, data analysts can discover insights by combining data in MongoDB with data from other operational and analytic data stores across the enterprise.Run Better Applications with Better DataThe ease of getting data into MongoDB from other enterprise and third party systems is critical to big data applications delivering trusted, complete, and relevant information to business users. Informatica ensures that users can access and integrate all of their data with MongoDB and other enterprise data to provide a complete picture.Lower Costs of Data IntegrationUp to 80% of the work in a big data project involves data integration and the resource skills to do the work are often in short supply. The good news is that organizations can staff big data projects with over 100,000 trained Informatica developers around the world. Informatica makes it easier to load and extract data into and from MongoDB using readily available resource skills thereby lowering ongoing operational costs.Deliver Business Impact with Rapid DeploymentMongoDB is the world's leading NoSQL database designed for ease of development and scaling. By providing a flexible schema, it makes application development truly agile. Informatica is a leading provider of data integration software. By providing a single, consistent data integration approach for all types of data including traditional relational structures, complex file formats, and flexible dynamic schemas such as in MongoDB, organizations are empowered to rapidly adopt MongoDB into their enterprise data management infrastructure for maximum business impact.
  • Recording of this webinar will be posted

Partner Webinar: Deliver Big Data Apps Faster With Informatica & MongoDB Partner Webinar: Deliver Big Data Apps Faster With Informatica & MongoDB Presentation Transcript

  • Deliver Big Data Apps Faster With Informatica & MongoDB John Haddad, Senior Director Big Data Product Marketing, Informatica Gaurav Pathak, Senior Product Manager Big Data, Informatica
  • 2014 2011 Devices & Machines 2007 Communities & Society 1990s Business Ecosystems 1980s BUSINESS 1960s-1970s USERS VALUE Few Employees Back Office Automation Customers/ Consumers Many Employees Front Office Productivity Line-of-Business Self-Service Social Engagement Real-Time Optimization E-Commerce TECHNOLOGIES OS/360 SOURCES TECHNOLOGY MAINFRAME 10 2 CLIENT-SERVER 10 4 WEB 10 6 CLOUD 10 7 SOCIAL 10 9 INTERNET OF THINGS 10 11
  • Informatica for MongoDB Applications BI / Analytic Apps Relational, Mainframe Data Warehouse & Data Marts Documents and Emails Social Media, Web Logs Machine Device, Cloud Access, integrate, transform, & ingest data into MongoDB Access, integrate, transform & ingest MongoDB data into other analytic systems (e.g. Hadoop, data warehouse)
  • Informatica for MongoDB Integrate and move data into MongoDB Applications Relational, Mainframe Customers table Customer Policies document Documents and Emails Policies table Social Media, Web Logs Machine Device, Cloud Access, integrate, transform, & ingest data into MongoDB
  • Informatica for MongoDB Integrate data on Hadoop for downstream analytics BI / Analytic Apps Orders table Relational, Mainframe Product content document Documents and Emails Data Warehouse & Data Marts Social Media, Web Logs Machine Device, Cloud Machine data Access, integrate, transform & ingest MongoDB data into other analytic systems (e.g. Hadoop, data warehouse)
  • Capabilities • • • • • • • • • High Productivity Development Environment Universal Data Access High-Speed Data Ingestion and Extraction Metadata Discovery for Flexible Data Models Embedded Entity Access JSON Document Handling Distributed Data Access through Read Preferences Map Once, Deploy Anywhere Unified Administration and High Availability
  • High Productivity Development Environment
  • Unleash the Power of Big Data With high performance Universal Data Access Messaging, and Web Services Relational and Flat Files Mainframe and Midrange Unstructured Data and Files MPP Appliances WebSphere MQ JMS MSMQ SAP NetWeaver XI Web Services TIBCO webMethods Oracle DB2 UDB DB2/400 SQL Server Sybase Informix Teradata Netezza ODBC JDBC ADABAS Datacom DB2 IDMS IMS VSAM C-ISAM Binary Flat Files Tape Formats… Word, Excel PDF StarOffice WordPerfect Email (POP, IMPA) HTTP Pivotal Vertica Netezza Flat files ASCII reports HTML RPG ANSI LDAP Teradata Aster JD Edwards SAP NetWeaver Lotus Notes SAP NetWeaver BI Oracle E-Business SAS PeopleSoft Siebel Salesforce CRM Force.com RightNow NetSuite ADP Hewitt SAP By Design Oracle OnDemand EDI–X12 EDI-Fact RosettaNet HL7 HIPAA Packaged Applications SaaS/BPO AST FIX SWIFT Cargo IMP MVR Industry Standards XML Standards XML LegalXML IFX cXML Facebook Twitter LinkedIn ebXML HL7 v3.0 ACORD (AL3, XML) Kapow Datasift Social Media
  • Metadata Discovery for Flexible Data Models • Schema Inference done by sampling the first “n” rows. • Performs a union of fields to create the representative schema. • Schema Information cached in either the Mongo instance or a file. 10
  • Embedded Entity Access 11
  • JSON Document Handling • Users can read • • and write JSON documents directly through DocumentAsJSON port. Filtering while Read is available for “Document as JSON” feature When writing to “DocumentAsJSO N” port, there is no schema constraint 12
  • Distributed Data Access through Read Preferences 13
  • The Value of a Virtual Data Machine (like Vibe): Integration Flexibility: Same skills, multiple deployment modes. • Skills leverage • Future proof investment • Development Acceleration Development Deployment Data Virtualization Cloud Desktop Server Data Federation Embedded DQ in apps Embedded data quality in apps Data Integration Hub Hadoop 14
  • Unified Administration Single Place to Manage & Monitor
  • Demo 16
  • Demo - Product Catalog Creation
  • Demo – Product Catalog Creation Applications • Sources • Read Music Data from a flat file • Read Books Data from Relational, Mainframe a Normalized Database Schema • Read Movies Data Documents and Emails Social Media, Web Logs from a JSON File Access, integrate, transform, & ingest data into MongoDB • Lookup • Lookup MongoDB for SKU details • Target • Write to Machine Device, Cloud ProductCatalog Collection in MongoDB
  • Demo – Batch Aggregation Applications BI / Analytic Apps • Sources • Read from Orders Collection in MongoDB • Transform • Aggregate Data Data Warehouse & Data Marts Access, integrate, transform & ingest MongoDB data into other analytic systems (e.g. Hadoop, data warehouse) or MongoDB itself based on Nation and ShipMode • Target • Write to Nation collection in MongoDB
  • Customer Benefits • • • • Discover Insights from Big Data Faster Run Better Applications with Better Data Lower Costs of Data Integration Deliver Business Impact with Rapid Deployment
  • Resources and Q & A http://bit.ly/mongodbbi • Configuring PowerExchange to connect to MongoDB at http://bit.ly/pwxmongodb1 • Create mappings that read and write to MongoDB at http://bit.ly/pwxmongodb2 • Write JSON documents directly to MongoDB at http://bit.ly/pwxmongodb3