IBM® PureData™ System for Analytics

IBM® PureData™ System for Analytics
Carlo Marchesi, PureData Specialist
[email protected]
February 13, 2013
© 2013 IBM Corporation
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© 2013 IBM Corporation
IBM PureData System for Analytics
Takes Analytics Beyond Reporting
Optimization
Predictive
Analytics
BI Reporting and
Ad-Hoc Analysis
 What is the best choice?
 What will happen?
 What happened?
 What will the impact be?
 When and where?
 How much?
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© 2013 IBM Corporation
Traditionelle Data Warehouse Anwendungen
sind einfach zu komplex
Sie basieren auf Datenbanken die für die Transaktionsverarbeitung
optimiert wurden – NICHT um die Anforderungen von
fortschrittlichen Analysen auf großen Datenbeständen abzubilden
 Zu komplexe Infrastruktur
 Zu ineffiziente Analysen
 Zu komplizierter Einsatz
 Zu viel Personal für die Wartung
 Zu viel Tuning notwendig
 Zu kostspielig im Betrieb
Zu zeitraubend für schnelle Antworten
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© 2013 IBM Corporation
IBM PureSystem Family
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Infrastructure
Application Platform
Data Platform
Delivering Infrastructure Services
Delivering Platform Services
Delivering Data Services
© 2013 IBM Corporation
IBM PureData System
Meeting Big Data Challenges – Fast and Easy!
For apps like E-commerce…
System for Transactions
Database cluster services optimized for
transactional throughput and scalability
For apps like Customer Analysis…
System for Analytics
Data warehouse services optimized for
high-speed, peta-scale analytics and simplicity
Powered by Netezza
technology
For apps like Real-time Fraud Detection…
System for Operational Analytics
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Operational data warehouse services optimized to
balance high performance analytics and real-time
operational throughput
© 2013 IBM Corporation
Built-In Expertise Makes This as Simple as an Appliance
 Dedicated device
 Optimized for purpose
 Complete solution
 Fast installation
 Very easy operation
 Standard interfaces
 Low cost
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© 2013 IBM Corporation
IBM PureData System for Analytics
The Simple Appliance for Serious Analytics
Built-in Expertise
No indexes or tuning
Data model agnostic
Hardware accelerated, fully parallel, optimized, In Database Analytics
Integration by Design
Server, Storage, Database in one easy to use package
Automatic parallelization and resource optimization to scale efficiently
and economically
Enterprise-class security and platform management
Simplified Experience
Up and running in hours
Minimal up front design and tuning
Minimal ongoing administration
Standard interfaces to best of breed Analytics, Business Intelligence, and
data integration tools
Built-in, complex analytical capabilities allow users to derive insight from
their data quickly
Easy connectivity to other Big Data Platform components
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© 2013 IBM Corporation
IBM PureData System for Analytics
Transforms the User Experience
 Purpose-built analytics engine
 Integrated database, server and storage
 Standard interfaces
 Low total cost of ownership
Speed: 10-100x faster than traditional systems
Simplicity: Minimal administration and tuning
Scalability: Peta-scale user data capacity
Smart: High-performance advanced analytics
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© 2013 IBM Corporation
Speed
15,000 Nutzer führen
800,000+ Abfragen am
Tag aus. Jetzt 50X
schneller als vorher
“…when something took 24 hours I could only
do so much with it, but when something takes
10 seconds, I may be able to completely
rethink the business …”
- SVP Application Development, Nielsen
Source: http://www.youtube.com/watch?v=yOwnX14nLrE&feature=player_embedded
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© 2013 IBM Corporation
Simplicity
Im produktiven Einsatz 6 Monate
vor dem ersten Training
200X schneller als das alte Oracle System
ROI in weniger als 3 Monaten
MONTHS
WEEKS
“Allowing the business users access to
the Netezza box was what sold it.”
DAYS
Steve Taff,
Executive Dir. of IT Services
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© 2013 IBM Corporation
Scalability
1 PB auf Netezza Systemen
7 Jahre an historischen Daten
100-200% jährliches
Datenwachstum
“NYSE … has replaced an Oracle IO relational database
with a data warehousing appliance from Netezza,
allowing it to conduct rapid searches of 650 terabytes
of data.”
ComputerWeekly.com
Source: http://www.computerweekly.com/Articles/2008/04/14/230265/NYSE-improves-data-management-with-datawarehousing.htm
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© 2013 IBM Corporation
Smart
30% redemption increase
“Using results derived from Netezza system,
Catalina Marketing is able to give shoppers
(more relevant) coupons at point of sale for
items they would like want to buy in future
visits.”
Editorial Director,
DM Review
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© 2013 IBM Corporation
Integrated by Design
IBM Netezza In-Database Analytics Version 2.0
Netezza
In-Database
Analytics
Transformations
Mathematical
Geospatial
Predictive
Statistics
Time Series
Data Mining
 No data movement
 Analyze deep and wide data
 High performance, parallel computation
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© 2013 IBM Corporation
Pre-Built In-Database Analytics
Statistics
 Descriptive Statistics+
 Distance Measures*
 Hypothesis Testing*
 Chi-Square &
Contingency Tables*
 Univariate &
Multivariate
Distributions+
Transformations
 Data Profiling /
Descriptive Statistics+
 General Diagnostics
Time Series
 Autoregressive+
 Forecasting*
 Statistics+
 Sampling
 Data prep
 Monte Carlo
Simulation*
Data Mining
Predictive
Mathematical
 Basic Math*
 Permutation and
Combination*
 Greatest Common
Divisor and Least
Common Multiple*
 Conversion of Values*
 Exponential and
Logarithm*
 Gamma and Beta
Functions
 Matrix Algebra+
 Area Under Curve*
 Interpolation Methods*
Geospatial
 Association Rules+
 Linear Regression+
 Geospatial Data Type
 Clustering+
 Logistic Regression+
 Geometric Functions
 Feature Extraction+
 Classification
 Geometric Analysis
 Discriminant
Analysis*
 Bayesian
 Sampling
* Fuzzy Logix
DB Lytix
capabilities
+ Netezza
Analytics and
Fuzzy Logix
DB Lytix
capabilities
 Model Testing
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© 2013 IBM Corporation
Combining Spatial and Corporate Data
Delivering More Insight
 Combine location with 100 Million
call data records
 Customer usage and location can
now be used together to
– Report on usage by area
– Develop new marketing campaigns
to gain customers in low usage areas
– Planning for additional towers and
network capacity
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© 2013 IBM Corporation
PureData System for Analytics Optimization With Other IBM Products
Big Data
Platform
Data
Integration
Business
Intelligence /
Performance
Management
System Z
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 InfoSphere Streams
 InfoSphere BigInsights
 System ML (Machine Learning)
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Information Server v9.1
InfoSphere Discovery v4.5
InfoSphere Data Architect v8.1
InfoSphere CDC Heterogeneous Replication
InfoSphere Optim Data Archive 9.1
Industry Models v8.4 – Banking, Insurance, Healthcare
Industry Model Packs – Supply Chain, Customer, Market & Campaign
Tivoli Storage Manager
Vivismo Data Explorer v8.2
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Cognos v10.2
Cognos TM1 v9.5
Guardium DB Monitoring v9
SPSS Modeler v15
Unica EMM Marketing Analytics 8.6
Unica NetInsights 8.6
 IBM DB2 Analytics Accelerator (IDAA)
 zLinux ODBC driver
Coming Soon:
PureData System for Operational
Analytics
Guardium
Informix Data Warehouse Edition
SPSS v16
© 2013 IBM Corporation
Loading the PureData System for Analytics
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JDBC
Data In
ODBC
Ab Initio
Cloudera
Composite Software
IBM Big Insights
IBM Information Server
IBM InfoSphere Streams
Informatica
Oracle Data Integrator
Oracle GoldenGate
SAP Business Objects
SQL
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OLE-DB
Data Integration
© 2013 IBM Corporation
Querying the PureData System for Analytics
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JDBC
Data Out
ODBC
IBM Cognos
IBM SPSS
IBM Unica
Information Builders
Kalido
KXEN
Microsoft Excel
MicroStrategy
Oracle OBIEE
SAP Business Objects
SAS
Actuate
SQL
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OLE-DB
Reporting and Analysis
© 2013 IBM Corporation
PureData System for Analytics Hardware Overview: Model N2001
12 Disk Enclosures
 288 600 GB SAS2 Drives
• 240 for User Data
• 14 for S-Blades
• 34 Spare
 RAID 1 Mirroring
2 Hosts (Active-Passive)
 2 6-Core Intel 3.46 GHz CPUs
 7x300 GB SAS Drives
 Red Hat Linux 6 64-bit
Scales from
½ Rack to 4
Racks
7 PureData for Analytics S-Blades™
 2 Intel 8 Core 2+ GHz CPUs
 2 8-Engine Xilinx Virtex-6 FPGAs
 128 GB RAM + 8 GB slice buffer
 Linux 64-bit Kernel
 User Data Capacity:
 Data Scan Speed:
 Load Speed (per system):
192 TB*
478 TB/hr*
5+ TB/hr
 Power Requirements:
 Cooling Requirements:
7.5 kW
27,000 BTU/hr
* Assuming 4X compression
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© 2013 IBM Corporation
Big Data Meets Deep Analytics
Analytics without constraint
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© 2013 IBM Corporation
PureExperience Program
Let Us Prove it at No Charge
1. Guided analysis of business value
2. PureSystems Technology Demonstration
3. On-Site Trial & Support
 Free execution of
on-site service engagement
 Continued use of the PureSystems
offering for 30 days
 Access to a technical advocate
for usage questions and advice
 Single point of IBM support and
maintenance
www.ibm.com/PureExperience
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© 2013 IBM Corporation
Take the next step
Discover the value and begin your journey with IBM PureSystems
 Visit ibm.com/puresystems to learn more
 Join the conversation about this new category
of computing
– Twitter: @IBM PureSystems
• Hashtag: #IBMPureSystems or #expertintsys
– YouTube Channel: expertintegratedsys
– Blog: expertintegratedsystemsblog.com
 Developers – Get started today with our no charge
trial offerings!
– ibm.com/developerworks/puresystems/try
 Explore PureSystem partner solutions
– Ibm.com/puresystems/centre
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© 2013 IBM Corporation