This presentation outlines the key cababilities of the Good Data analytical platform. It also describes the platform's cloud-based architecture.

1. Good Data:
Collaborative Analytics On Demand
Zdenek Svoboda, Vice President, Products
Jakub Nesetril, Senior Director of User Experiences
May 18, 2009
Monday, May 18, 2009

2. Agenda
• Good Data Introduction
• BI Challenges
• Product Demo
• Architecture
Monday, May 18, 2009

3. Good Data: Business Intelligence in One Week
Monday Tuesday Wednesday Thursday Friday
Create & Create & Publish &
Extract & Load &
Adjust Adjust Share
Transform Cleanse
Analytical Reports / Reports /
Data Data
Model Dashboards Dashboards
AGILE ITERATION
Monday, May 18, 2009

4. Traditional Approaches Oſten Fail to Deliver BI Projects
Traditional Good Data
Project Cost $$$$$ $$
Time to success 6-12+ months weeks
Deployment enterprise on demand service
Analysis & software / SaaS
Implementation waterfall agile
Per user cost $100s-$1000s $10s (free for many)
Scalability < 10 projects 1000s of projects
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Monday, May 18, 2009

5. Product Demo
Monday, May 18, 2009

6. Good Data Architecture
Clients API Cloud Execution Cloud Storage Cloud
Metadata Report On Demand
AJAX Client Server Executor Caches
(Collaboration,
Analytics, Async
HTTP Report ETL
Dashboard, Queue IP
REST Results Executor
Reporting) Storage
PDF/XLS Report
Or Results Exporter
Storage
3rd Party App Report
Pivoting
Admin
Common services: security, load balancing, routing etc.
Amazon Web Services - EC2, EBS, S3
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Monday, May 18, 2009

7. Good Data Architecture
Storage Cloud
On Demand
Caches
• DB not designed for the cloud
• DBMS distribution mechanism = clustering
Storage • Disk is slow, in memory very fast
• Memory still scarce
• Processing on stateless instances is hard
Storage
7
Monday, May 18, 2009

8. Good Data Query Processing
(under development)
Data Integration 1 2 3 4
Distributed
ETL 1 2 3 4
1 2 3 4
In-memory
data processor
1 2 3 4
1 2 3 4
1 2 3 4
Query 1 2 3 4
Query
Manager In-memory
data processor 5 6 7 8
5 6 7 8
3 2 3 4 5 6 7 8
Amazon Elastic Data Storage
MapReduce (partitioned, columnar,
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(Hadoop) compressed)
Monday, May 18, 2009

9. Economics of Cloud Computing
Make Good Data Possible
Cheaper
Processing • Cloud makes ROLAP possible
Power • Parallel: 1 CPU x 20 hours = 20 CPUs x 1 hour
Elastic Scale • BI is very sensitive to unpredictable load
• IT builds for peak load, we don’t have to
Massive Multi-
Tenancy • Single instance across 1000s of customers
Service-Oriented
• Transient HW nodes
(stateless design) • Massive load balancing (shared nothing)
• Amazon S3 and EBS are the only persistence 9
Monday, May 18, 2009

10. Text
Sign up for free today!
www.gooddata.com 10
Monday, May 18, 2009