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© 2011 IBM Corporation Information Management IBM Data Warehousing and Analytics Portfolio Summary IBM Information Management Mike McCarthy IBM Corporation [email protected]
© 2011 IBM Corporation
Information Management
IBM Data Warehousing and Analytics Portfolio Summary
IBM Information Management
Mike McCarthy
© 2011 IBM Corporation
Information Management
IBM Information Management Portfolio
© 2011 IBM Corporation
Information Management
Current Data Warehouse Architecture
3
Source Systems
External Sources
External Sources
BillingBilling
HRHR
ERPERP
CRMCRM
Data Marts
Enterprise Data Warehouse
Data SourceData Source
DataIntegration
Data SourceData Source
© 2011 IBM Corporation
Information Management
IBM’s Logical Data Warehouse Architecture
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Features
� Application and workload optimized appliances and systems
� Fast data movement and integration
� Data governance and lifecycle management
� Framework for integrated managementNetezza
BI + Analytics
Smart Analytics System
Operational Analytics
Netezza High CapacityApplianceQueryable Archive
InfoSphere Streams
StreamProcessing
InfoSphere BigInsights
Big Data Processing
EnterpriseData Hub
© 2011 IBM Corporation
Information Management
IBM Warehouse Software
IBM Smart Analytics System
IBM Netezza
FlexibilitySimplicity The right mix of simplicity and flexibility
Simplicity, Flexibility, ChoiceIBM Data Warehouse & Analytics Solutions
Information Management Portfolio
(Information Server, MDM, Streams, etc)
Warehouse Accelerators
Custom Solutions
© 2011 IBM Corporation
Information Management
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� Purpose-built analytics engine
� Integrated database, server and storage
� Standard interfaces
� Low total cost of ownership
� Speed: 10-100x faster than traditional system
� Simplicity: Minimal administration and tuning
� Scalability: Peta-scale user data capacity
� Smart: High-performance advanced analytics
IBM NetezzaThe true data warehousing appliance
© 2011 IBM Corporation
Information Management
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� Integrated Cognos Business Intelligence
� Integrated InfoSphere Warehouse
� Integrated Information Server
� In-database cubing and mining
� Choice of platform and OS
Smart Analytics SystemThe modular system for business analytics
� Scale ‘On Demand’
� Modular application interfaces
� Built for complex and mixed workloads
� Autonomic tuning
© 2011 IBM Corporation
Information Management
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Extracting insight from an immense volume, variety and velocity of data, in context, beyond what was previously possible.
The Big Data Opportunity
Manage the complexity of multiple relational and non-relational data types and schemas
Streaming data and large volume data movement
Scale from terabytes to zettabytes
Variety:
Velocity:
Volume:
© 2011 IBM Corporation
Information Management
InfoSphere Streams
A platform for real-time analytics onbig data in motion
� Volume–Terabytes per second–Petabytes per day
� Variety–All kinds of data–All kinds of analytics
� Velocity–Insights in microseconds
� Agility–Dynamically responsive –Rapid application development
Millions of events per
second
Microsecond Latency
Traditional / Non-traditional data sources
Real time decisions
PowerfulAnalytics
Algo Trading
Telco churnpredict
SmartGrid
CyberSecurity
Government /Law enforcement
ICUMonitoring
EnvironmentMonitoring
© 2011 IBM Corporation
Information Management
InfoSphere BigInsights
A platform for analytics onbig data at rest
� Volume–Petabyte range
� Variety–All kinds of data–All kinds of analytics
Traditional / Non-traditional data sources
© 2011 IBM Corporation
Information Management
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Data continues to
expand exponentially.Analytics are becoming more complex as
business demands faster answers.The right infrastructure
is now mission critical to compete on analytics.
IBM Confidential
