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BI in the Cloud – Sky is the limit
BI in the Cloud – Sky is the limit Vishal Agrawal Product Technical Architect Infosys Tech Ltd Anand Govindarajan Principal Technology Architect Infosys Tech Ltd Current state of BI systems • Key characteristics – – – – – – High infrastructure requirements Unpredictable load High upfront investment High development & maintenance costs Longer duration for provisioning Dependency on IT • Issues – Limited adoption – Longer cycle time for BI application – Restricted Availability Cloud BI systems Benefits • • • • • • • Utility model of computing Lower entry and maintenance costs Massive processing power on-demand Faster time to develop applications Reduced Risk Multiple ways to consume the BI capability Multiple deployment and delivery models Cloud BI Systems Scenarios • • • • • • Short lived BI projects Quick prototyping BI systems for small & medium businesses Enterprise BI applications Data mining Custom applications (e.g. Web 2.0, Mobile application etc) Cloud BI delivery models • Public Cloud – SaaS (Software as a Service) – PaaS (Platform as a Service) – IaaS (Infrastructure as a Service) • Private Cloud • Hybrid Cloud Cloud BI delivery models Public cloud - SaaS • Key characteristics – Prepackaged end to end BI solution on the cloud – Easy management – Easy integration of the enterprise and external data – Unlimited auto scaling – Easy to implement (within days, weeks) – Business focus (CRM) – Multiple vendors available to choose from Cloud BI delivery models Public cloud - SaaS • Challenges – Security – No flexibility in choosing vendors for specific parts of your solution – No flexibility in design – Not suitable for custom applications • Usage scenarios – Short lived BI projects – BI systems for small & medium businesses Cloud BI delivery models Public cloud - PaaS • Key characteristics – Enabling platform available on the cloud – Pay per use for the services – Unlimited on demand scaling – Automated software updates – Flexibility in design – Focus only on the design, development – Low entry costs – Choice of multiple vendors Cloud BI delivery models Public cloud - PaaS • Challenges – Need to design & develop the application – Security • Usage scenarios – Custom applications – Enterprise BI systems – BI systems for small & medium businesses – Data Mining – Prototyping – Short lived BI projects Cloud BI delivery models Public cloud - IaaS • Key characteristics – Deploy own solution on the cloud – Pay for the Infrastructure used (Need not procure the hardware) – Unlimited on demand scaling – Complete Flexibility in design – Easier Cloud porting – Best of Breed solutions (can choose best options for – Infrastructure, DB, BI) – Low upfront costs Cloud BI delivery models Public cloud - IaaS • Challenges – Manageability – Need to design, develop the solution (more development time) – Need to pay upfront software licensing fee – Building horizontal scaling in the application • Usage scenarios – – – – – Enterprise BI systems Data mining Custom Applications Prototyping Short lived BI projects Cloud BI delivery models Private cloud • Key characteristics – Deploy the solution on the private cloud (own data center) – On demand scaling – Save the Infrastructure cost (by sharing the resources across applications) – Complete Flexibility in design – Complete control on the security Cloud BI delivery models Private cloud • Challenges – Manageability – Need to design, develop the solution (more development time) – Building horizontal scaling in the application – Higher upfront cost • Usage scenarios – – – – Enterprise BI systems Data mining Prototyping Short lived BI projects Cloud BI delivery models Hybrid cloud • Key characteristics – Deploy the predictable load on the private cloud (own data center) – Push unpredictable spikes on the public cloud – On demand scaling – Optimize the Infrastructure cost – Complete Flexibility in design – Better control on the security (keep the confidential data in the private cloud) Cloud BI delivery models Hybrid cloud • Challenges – Manageability – Need to design, develop the solution (more development time) – Building horizontal scaling in the application • Usage scenarios – Enterprise BI systems – Data mining – Prototyping – Short lived BI projects Current State of the BI market place • SaaS – Good data, Pivotlink, LogiXML, Pentaho • PaaS – Business Objects, SAS, Microsoft Azure, Vertica, Greenplum, Google apps Current State of the BI market place • IaaS – Infrastructure • AWS, Rackspace, GoGrid – Cloud Management • Elastra, Rightscale – DB/DW • MySQL, Oracle, SQL server, – BI • JasperReports, Pentaho Conclusion • • • • Cloud BI is set to change the BI landscape Lower the entry barriers for the organizations Result in much better adoption of BI systems Result in new innovations References • The Case for Data Warehousing-in-the-Cloud http://esj.com/articles/2009/06/17/dw-cloud.aspx • Business Intelligence in the Clouds http://www.informationmanagement.com/infodirect/2009_111/100150461.html • When to Implement BI in the Cloud http://portals.tdwi.org/blogs/wayneeckerson/2009/06/i mplementing-bi-in-the-cloud.aspx • BI SaaS Vendors Are Not Created Equal http://www.informationmanagement.com/blogs/business_intelligence_bi_soft ware_as_a_service_saas-10016138-1.html © 2009 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
