1. technology and computing

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
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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
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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
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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
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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
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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
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