smarter computing big data
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Smarter Computing
Understand the likely impact of Stream Computing and Big Data on your Business and Data CenterHow to control costs, improve performance, and mitigate risk throughout the data lifecycle
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Efficient &Innovative
Innovative
but …
Fueled sprawl & increased TCO
Efficient
but …
Limited access & flexibility
• Insatiable Demand
• Unsustainable Economics
• New Technologies
Entering New Era of Computing Driven by…
CentralizedComputing
DistributedComputing
SmarterComputing
IT needs to reinvent itself in order to enter this new era of computing
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AnalyzeIntegrate
Transactional & Collaborative Applications
Manage
Business Analytics Applications
External Information Sources
Cubes
Streams
Big Data Master
Data
Content
Data
StreamingInformation Govern
Quality Security & PrivacyLifecycle
Data Warehouses
Standards
The information supply chain
Content Analytics
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“
10xGrowth in digital data every 5 years
5%New Information that is structured
4 Billion# of cell phone users worldwide
2 Billion# of Internet users worldwide
When physical assets such as cell phones, traffic sensors, cameras, PCs, RFID tags etc. become elements of an information system with ability to capture, compute and communicate
information themselves on a massive sensor scale using common TCP/IP protocol.
-- Internet of Things by McKinsey Global Institute, 2010 “
The Industrial Revolution of Data.
-- Dr. Joe Hellerstein, UC Berkeley
What is ‘BIG’ Data
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Stock market• Impact of weather on
securities prices• Analyze market data at
ultra-low latencies
Fraud prevention• Detecting multi-party fraud• Real time fraud prevention
e-Science• Space weather prediction• Detection of transient events• Synchrotron atomic research
Transportation• Intelligent traffic
management
Manufacturing• Process control for
microchip fabrication
Natural Systems• Wildfire management• Water management
Telephony• CDR processing• Social analysis• Churn prediction• Geomapping
Other• Smart Grid• Text Analysis• Who’s Talking to Whom?• ERP for Commodities• FPGA Acceleration
• Real-time multimodal surveillance• Situational awareness• Cyber security detection
Law Enforcement, Defense & Cyber Security
Health & Life Sciences• Neonatal ICU monitoring• Epidemic early warning
system• Remote healthcare
monitoring
The opportunity for real-time analytic processing is everywhere …
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Operational Databases
Reporting and human analysis on historical data
Data at rest
1968Hierarchical database
1970 Relational database
OLTPOnline Transaction Processing
Data in Motion
Real Time Analytic Processing (RTAP) to improve business response
Stream Computing
2003
RTAP‘Real-Time’ Analytical Processing
Analysis of historic data to improve business transactions
Data Warehousing
1983 DB2 v1
OLAPOnline Analytical Processing
Evolution of technology frontiers
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• Manage and benefit from massive and growing amounts of data• Handle uncertainty around format variability and velocity of data• Handle unstructured data• Exploit BIG Data in a timely and cost effective fashion
Collect Manage
Integrate Analyze
COLLECT MANAGE
INTEGRATE ANALYZE
The Big Data Challenge
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Persistent Data
In-Motion Data
TraditionalData
Non-TraditionalData
Streams reuses InfoSphere
Warehouse or SPSS Analytic
models
Streams filters incoming data
BigInsights
WAREHOUSE
IBM offers a comprehensive and integrated set of solutions for many types of BIG Data processing needs
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Data Sources
BigInsights
Data can flow into one or more of the environments (even simultaneously)
User results
WAREHOUSE
The Big Data ecosystem: Interoperability is key
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Non-
Traditional /
Non-
Relational Data Sources
In-MotionAnalytics
Traditional / Relational Data
Sources
DatabaseAt-Rest DataAnalytics
Results
TraditionalAnalytics
StreamAnalytics
Ultra LowLatency Results
OLAP / OLTP
RTAP
IBM InfoSphere Streams
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• Deal with Gigabytes of data each second
• Work with application, sensor and internet data, video/audio
• Deliver insight in microseconds to analytical applications
• Support complex scenarios using C++ or Java code
• Integrate with existing analytics & data warehousing investments
Millions of events per
secondMicrosecond
Latency
Traditional / Non-traditional data sources
Real-time delivery
PowerfulAnalytics
AlgoTrading
Telco churnpredict
SmartGrid
CyberSecurity Government /
Law enforcement
ICUMonitoring
EnvironmentMonitoring
InfoSphere Streams for companies who need to …
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Now
Real-timeAnalytics
Real-time Window
Custom Visualizations
Real-time Data (Traffic Capture, Alerts, Logs, …)
IBM Commercially SensitiveAggregated Past
Aggregated TRAFFIC + DNS + Secondary Information
Retain Aggregate + Results
PCAP/Netflow
PCAP/ Netflow
Alerts etc.Alerts
Data-at-restAnalytics
Data-At-Rest Window
BigInsights
Cyber security example – Detecting botnets
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Integrate Automate Secure
• Scale to petabytes and thousands of users
• Deep integration with Cognos and SPSS
• Integrated analysis and analytic model consistency
IBM is uniquely positioned to help organizations handle their “BIG Data” analysis and management challenges
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Thank You! ibm.com/smartercomputing
Automate
Integrate SecureEfficient and Innovative IT for Improved Economics
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