IBM Data Warehousing and Analytics Portfolio Summary

Transcription

1 IBM Information Management IBM Data Warehousing and Analytics Portfolio Summary Information Management Mike McCarthy IBM Corporation

2 IBM Information Management Portfolio

3 Current Data Warehouse Architecture Source Systems CRM ERP Data Integration Enterprise Data Warehouse HR Billing External Sources Data Marts Data Source Data Source Data Source Data Source 3

4 IBM s Logical Data Warehouse Architecture InfoSphere BigInsights Big Data Processing Features Smart Analytics System Operational Analytics Enterprise Data Hub InfoSphere Streams Stream Processing Application and workload optimized appliances and systems Fast data movement and integration Data governance and lifecycle management Netezza BI + Analytics Netezza High Capacity Appliance Queryable Archive Framework for integrated management 4

5 Simplicity, Flexibility, Choice IBM Data Warehouse & Analytics Solutions IBM Netezza IBM Smart Analytics System IBM Warehouse Software Custom Solutions Warehouse Accelerators Information Management Portfolio (Information Server, MDM, Streams, etc) Simplicity The right mix of simplicity and flexibility Flexibility

6 Information Management IBM Netezza The true data warehousing appliance 6 Purpose-built analytics engine Integrated database, server and storage Standard interfaces Low total cost of ownership Speed: x faster than traditional system Simplicity: Minimal administration and tuning Scalability: Peta-scale user data capacity Smart: High-performance advanced analytics

7 Information Management Smart Analytics System The modular system for business analytics 7 Integrated Cognos Business Intelligence Integrated InfoSphere Warehouse Integrated Information Server In-database cubing and mining Choice of platform and OS Scale On Demand Modular application interfaces Built for complex and mixed workloads Autonomic tuning

8 The Big Data Opportunity Extracting insight from an immense volume, variety and velocity of data, in context, beyond what was previously possible. Variety: Velocity: Volume: Manage the complexity of multiple relational and nonrelational data types and schemas Streaming data and large volume data movement Scale from terabytes to zettabytes 8 8

9 InfoSphere Streams A platform for real-time analytics on big 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 ICU Monitoring Algo Trading Real time decisions Powerful Analytics Cyber Security Government / Law enforcement Environment Monitoring Smart Grid Traditional / Non-traditional data sources Telco churn predict Microsecond Latency

10 InfoSphere BigInsights A platform for analytics on big data at rest Volume Petabyte range Variety All kinds of data All kinds of analytics Traditional / Non-traditional data sources

11 Data Analytics The continues right are infrastructure becoming to more complex as expand business is now mission exponentially. demands critical faster to compete answers. on analytics. 11 IBM Confidential