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Tuesday August 4, 2009 Stephen Dine Datasource Consulting, LLC
2 Agenda  Cloud fundamentals  Demo of BI in the EC2 Cloud  Benefits to BI in the Cloud  Cloud challenges  New Technologies  Summary
3
4
5 Example Cloud Architecture Dynamic Infrastructure Software Virtual Server Containers Commodity Hardware Infrastructure ,[object Object],Ready for the Enterprise”: 3/7/08
6 Example BI Server Architecture (9pm)
7 Example BI Server Architecture (2am)
8 Example BI Server Architecture (4am)
9 Example BI Server Architecture (10am)
10 Demo of BI in the Cloud
11 Top Cloud Concerns
12 Quelling Security Concerns Physical & logical security Hidden data centers, cameras, biometric access, advanced alarm system Hypervisor paravirtualization Network security All server ports closed by default Traffic monitoring, SSH External security Network key encryption, multiple access keys, security groups
13 Benefits to BI in the Cloud  Flexibility to scale computing resources with few barriers  Ability to shorten BI implementation windows  Reduced cost for BI programs  Ability to add environments for testing, proof-of-concepts and upgrades   Geographic scalability
14 Amazon EC2 Instance Pricing * EC2 Compute Unit (ECU) – One EC2 Compute Unit (ECU) provides the equivalent CPU capacity of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor.
15 Challenges to BI in the Cloud The ability to scale-up is limited Difficult to quell security concerns Viability of moving large amounts of data Performance of physical data access Reliability of service concerns Pricing is variable and complex
16 Lessons Learned (thus far…)  Shared development can be a challenge  Dynamically provisioning servers requires configuration  scripts upon startup  Keep your ear to the ground as technology and landscape changes rapidly  Persistence is important architectural consideration  Consistent image naming standards are critical
17 Conclusions Deploying BI in the Cloud can help programs become more flexible, scalable and agile Cloud service architectures and vendors that provide them are still immature and is best suited for sandbox, development and test environments It can be challenging to configure databases and BI tools to run in the Cloud The Cloud holds a great deal of potential to change the way that we deliver BI to the masses
18 Special Thanks to: Ray Light, Director of Product Marketing, GoodData (www.gooddata.com) Dave Menninger, VP Marketing & Product Management,  Vertica (www.vertica.com) Ken Rudin, CEO & Co-founder, LucidEra (www.lucidera.com) John Thompson, CEO, North America, Kognitio (www.kognitio.com)
19 Contact Information If you have further questions or comments: Steve Dine President, Datasource Consulting, LLC sdine@datasourceconsulting.com 303-931-1046
20 Example: EC2 Charges

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Business Intelligence In The Cloud

  • 1. Tuesday August 4, 2009 Stephen Dine Datasource Consulting, LLC
  • 2. 2 Agenda Cloud fundamentals Demo of BI in the EC2 Cloud Benefits to BI in the Cloud Cloud challenges New Technologies Summary
  • 3. 3
  • 4. 4
  • 5.
  • 6. 6 Example BI Server Architecture (9pm)
  • 7. 7 Example BI Server Architecture (2am)
  • 8. 8 Example BI Server Architecture (4am)
  • 9. 9 Example BI Server Architecture (10am)
  • 10. 10 Demo of BI in the Cloud
  • 11. 11 Top Cloud Concerns
  • 12. 12 Quelling Security Concerns Physical & logical security Hidden data centers, cameras, biometric access, advanced alarm system Hypervisor paravirtualization Network security All server ports closed by default Traffic monitoring, SSH External security Network key encryption, multiple access keys, security groups
  • 13. 13 Benefits to BI in the Cloud Flexibility to scale computing resources with few barriers Ability to shorten BI implementation windows Reduced cost for BI programs Ability to add environments for testing, proof-of-concepts and upgrades Geographic scalability
  • 14. 14 Amazon EC2 Instance Pricing * EC2 Compute Unit (ECU) – One EC2 Compute Unit (ECU) provides the equivalent CPU capacity of a 1.0-1.2 GHz 2007 Opteron or 2007 Xeon processor.
  • 15. 15 Challenges to BI in the Cloud The ability to scale-up is limited Difficult to quell security concerns Viability of moving large amounts of data Performance of physical data access Reliability of service concerns Pricing is variable and complex
  • 16. 16 Lessons Learned (thus far…) Shared development can be a challenge Dynamically provisioning servers requires configuration scripts upon startup Keep your ear to the ground as technology and landscape changes rapidly Persistence is important architectural consideration Consistent image naming standards are critical
  • 17. 17 Conclusions Deploying BI in the Cloud can help programs become more flexible, scalable and agile Cloud service architectures and vendors that provide them are still immature and is best suited for sandbox, development and test environments It can be challenging to configure databases and BI tools to run in the Cloud The Cloud holds a great deal of potential to change the way that we deliver BI to the masses
  • 18. 18 Special Thanks to: Ray Light, Director of Product Marketing, GoodData (www.gooddata.com) Dave Menninger, VP Marketing & Product Management, Vertica (www.vertica.com) Ken Rudin, CEO & Co-founder, LucidEra (www.lucidera.com) John Thompson, CEO, North America, Kognitio (www.kognitio.com)
  • 19. 19 Contact Information If you have further questions or comments: Steve Dine President, Datasource Consulting, LLC sdine@datasourceconsulting.com 303-931-1046
  • 20. 20 Example: EC2 Charges