business intelligence in the cloud

Stephen Dine

Datasource Consulting, LLCTuesday

August 4, 2009

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Cloud fundamentals

Demo of BI in the EC2 Cloud

Benefits to BI in the Cloud

Cloud challenges

New Technologies

Summary

Agenda

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Example Cloud Architecture

• Source: Forrester Research: “Is Cloud Computing Ready for the Enterprise”: 3/7/08

Dynamic Infrastructure Software

Virtual Server Containers

Commodity Hardware Infrastructure

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Example BI Server Architecture(9pm)

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Example BI Server Architecture(2am)

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Example BI Server Architecture(4am)

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Example BI Server Architecture(10am)

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Demo of BI in the Cloud

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Top Cloud Concerns

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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

Quelling Security Concerns

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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

Benefits to BI in the Cloud

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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.

Instance Type & RAM

CPU (Virtual Cores x ECUs) HD

Per CPU Hour

24/ 7CPU per

Month

Base Month Price

4/ 5CPU per

Month

Base Month Price

Small Win 32-Bit 1.7GB

1 x 1 160GB $0.125 720 Hours

$90.00 80 Hours

$10.00

Large Win 64-Bit 7.5GB

2 x 2 850GB $0.50 720 Hours

$360.00 80 Hours

$40.00

X-large Win64-Bit 15GB

4 x 2 1,690GB $1.00 720 Hours

$720.00 80 Hours

$80.00

High CPUMed Win

32-Bit 1.7GB

2 x 2.5 350GB $0.30 720 Hours

$216.00 80 Hours

$24.00

High CPU X-Large Win 64-Bit 7GB

8 x 2.5 1,690GB $1.20 720 Hours

$864.00 80 Hours

$96.00

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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

Challenges to BI in the Cloud

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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

Lessons Learned (thus far…)

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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

Conclusions

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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)

Special Thanks to:

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Contact Information

• If you have further questions or comments:

Steve Dine

President, Datasource Consulting, LLC

sdine@datasourceconsulting.com

303-931-1046

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Example: EC2 Charges