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)
Public Cloud SaaS (Software as a Service) PaaS (Platform as a Service) IaaS (Infrastructure as a Service) Private Cloud Hybrid Cloud
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
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
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
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
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
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
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
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
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)
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 BI MySQL, Oracle, SQL server, 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.information- management.com/infodirect/2009_111/10015046-1.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
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