Analytics on system z final

© 2015 IBM Corporation
zAnalytics
DB2 Update Day, March 2015
1
DB2 Update 2015

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Status 2015
Iceland, Reykjavik, Nyherii 13 17-3-15
Finland Helsinki, IBM 51 23-3-15
Norway, Oslo, Evry 59 24-3-15
Sweden, Stockholm, SEB 118 25-3-15
Denmark, Copenhagen, DB 109 26-3-15
Denmark Silkeborg, SD/JB 53 27-3-15
Total 403
DB2 for developers, architects, DBAs and other good people
who really appreciate the strongest relational database in the world.

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Agenda
DB2 Use Cases - Trends and directions
coffee
DB2 Archives / DB2 Table Archives and others – comparison
Managing DB2 with IBM Admin & Compare for System z /
Update on functionality & Customer UseCase
Lunch
DB2 11 Update for Developers
coffee
Native Stored Procedures / SQL/PL for DB2 11 / Revisiting
Native Stored Procedures & SQL/PL
Closure

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IBM z Systems Mobile Enablement
Focus on Information
and Analytics
Peter Schouboe
IBM zAnalytics, Nordic
Schouboe@dk.ibm.com

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Agenda
Mobile affects IT and need for Analytics
Some infrastructure notes on z Systems
Analytics on z Systems
– Reporting
• QMF
• Cognos
– Forecasting
• SPSS
– Decision support
• ILOG
Summary

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Mobile pervasiveness is demanding higher service levels
6
91% 75% 96% 90% 900%
mobile users keep
their device within
arm’s reach 100%
of the time
mobile shoppers
take action after
receiving a location
based message
year to year
increase in mobile
cyber Monday sales
between 2012
and 2011
users use multiple
screens as
channels come
together to
create integrated
experiences
increase of global
machine-to-machine
connections by 2022
(2 billion in 2011 to
18 billion at the
end of 2022)
© 2013 IBM Corporation6

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Mobile changes the business landscape
Finance & Banking
Manage their investment
portfolios and accounts from
anywhere for complete bank
transactions
Insurance
File, process and
manage claims and
document damages
as they happen
Travel & Transportation
Provide up to date
information specific to their
itineraries and location and
enable customer self-service
Construction & Manufacturing
Manage complex projects
and operations on site
and streamline survey
and work order processes
Retail
Engage shoppers in new
ways and intelligently target
personalized and location
sensitive marketing offers
Cross-Industry CIO’’’’s Office
Empower employees with anytime,
anyplace access to dashboards and
critical information
Mobile data traffic will grow at 61%(CAGR) 2013 to 2018
Where will it be stored ? How will it be manage & processed?

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Mobile computing driving real-time and 24/7 business analytics
z Systems Hybrid Transaction and Analytics Platform supporting the mobile experience
Business execs need to know the
health of their business 24/7/365
The “mobile office” supporting timely,
confident decision making - delivering
business insight any time any where
Mobile drives real time business
analytics
Customer experience influenced by
content -geo-specific offers and
service offers ‘as-you-need them’
e.g. while consumers are in the store
(the “mobile-moment”)
Systems of
engagement
need a secure,
scalable, always-on
System of
Record

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9

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Mobile workloads impact systems of record
differently than web workloads.
Increase in off-peak transactions. Expect 10-
50% growth as you add a mobile channel.
Increased query or “read-only” transactions. As
many as 50% of mobile transaction could be
“read-only”.
Unanticipated spikes in workload due to popular
apps, features or special offers. No traditional
times for workload spikes.
Inefficient applications written by “non-
professional” coders. Drives up transaction
rates unnecessarily.

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Agenda
– Reporting
• QMF
• Cognos
– Forecasting
• SPSS
• ILOG
Summary

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Complex IT infrastructure Issues
- performance issues, delays, errors, hard to debug, expensive to maintain…..

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System z
PR/SM
Hipersockets
Crypto functions
zSystems and Analytical Application Workloads on zLinux.
CPU
CPU
CPU
zVM
zLinux
zLinux
zLinux
zLinux
zLinux
zLinux
zLinux
zLinux
DB2 UDB Cognos
IFL
IFL
IFL
IFL
IFL
IFL
SPSS Data Mart
zIIP
CPU
CPU
zIIP
zIIP
LPAR1
z/OS
LPAR2
z/OS
Analytical Workload
Operational BI
DB2/z IDAA link
CICS CICS
Transaction Workload
• Unlimited number of
Linux clients
• 100% utilization on IFL
• Shared everything
(Memory, Discs, CPU)
• No Network latency
• IFL’s on max capacity
• Box upgrade includes
new IFLs – at no cost
• Only zOS CPs counts in
MLC/OTC
• zIIP offload on DB2 Use
from zLinux
IDAAHTAP
Query

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* No server can fully exploit its
maximum I/O bandwidth
PCI – Processor Capacity
Index (IBM MIPS)
141-way
Customer Processors
PCI for
1-way
1695
Memory
10 TB
System I/O Bandwidth
832 GB/Sec*
80-way
64-way
54-way
1.5
TB
512
GB 1202902600
288 GB/sec*
172.8 GB/sec*
1514
3
TB
384 GB/Sec*
101-way
z10 EC
z9 EC
z196
zEC12
z13
IBM z13: Advanced system design optimized for digital
business

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• Right-time insight at point of impact
• Increased business agility
• Improved data governance and
security
• Reduced infrastructure cost and
complexity
Transactions
Analytics
And - a new Strategy for the new type of Analytics is
required….
IBM/Gartner named it Hybrid Transaction-Analytical
Processing (HTAP)
GARTNER:
“By eliminating analytic latency and data synchronization issues, hybrid
transaction/analytical processing will enable IT leaders to simplify their information
management infrastructure”
“This architecture will drive the most innovation in real-time analytics over the next 10
years via greater situation awareness and improved business agility”
Gartner Research Note G00259033: Gartner 01-2014 Hybrid Transaction Analytical Processing Will Foster Opportunities

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DATA
Transaction
Data
Customer Data
Account Data
Payment Data
Claims Data
System z Host:
System z
Orchestration
Analytics:
Predictive &
Descriptive
Business
Rules
network
network
Key Characteristics
DATA
Transaction
Data
Customer Data
Account Data
Payment Data
Claims Data
System z Host:
System z
Orchestration
Analytics:
Descriptive &
Predictive
Business
Rules
WHY?
• System z already hosts a majority of the systems of
record data that feeds business analytics
• Unparalleled, proven performance execution of
combining transactional data environments, analytics &
rules
• Best of breed security for sensitive data
• Extensive logging for data and transaction governance
• Existing comprehensive, tested HA / DR capabilities
• Cost savings from reduced systems, software & people
• Plug and play capacity extensions and migrations
enabling quick production application deployment with
no downtime
High Level Strategy: Bring Analytics
to the Data
Much operational data resides on z/OS
– Many customers ETL this data to other
platforms for analytics
– ETL: Expensive, error prone, security
concerns,
data not current, multiple copies
ETL can be avoided
Integrated Transaction and Analytics
Processing
– OLTP and analytics in the same database

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IBM DB2 Analytics Accelerator
Enhanced with PureData System for Analytics N3001
Benefits
Extreme performance for complex queries
- Up to 2000x performance improvements
Cost Savings
- Offload complex queries and eliminate
costly query tuning
- No need to create or maintain indices
- Improves access to and lowers the cost of
storing, managing and processing historical
data
Integrated with DB2 z/OS and inherits
mission critical features such as security and
recoverability
Access to DB2 Analytics Accelerator is
transparent to applications and users
Fast deployment and time to value
- Installation is non-disruptive
- Plug it in, load data and go in 1-2 days
A high performance
appliance that integrates
Netezza technology with
zEnterprise technology to
deliver dramatically faster
business analysis
Highlights – What’s New?
The PureData System for Analytics N3001
provides additional benefits to DB2 Analytics
Accelerator customers:
Advanced security through encryption of data
at rest with self-encrypting disks
Performance improvements for analytic
workloads
Improved serviceability with the recently
introduced automatic call home capability
17

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DB2 Analytics Accelerator Roadmap
ISAO V1
Query
Accelerator
Storage Saver
Advanced
Analytics
Unified
Store
2011
2012/2013/2014
SPSS & HADOOP
Integration integration
Accelerating in-
database
transformation
Sophisticated
multi-temperature data
and archiving solution
• Enhancing current capabilities
• Enabling more query acceleration
• Increasing transparency
• Supporting new use cases
• Utilizing PDA technology advantages
IDAA V2.1 (11/2011
•Netezza acceleration
IDAA V3.1 (11/2012)
•Incremental Update
•Storage Saver
IDAA V4.1 (11/2013)
•Static SQL
•Workload balance
IDAA V4.1 PTF 5 (04/2015)
•In-database transformation
•Incremental Update Turbo
IDAA V4.1 PTF 4 (10/2014)
•Encryption of data at rest
•Call Home
ELT
Accelerator
2015

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How we enable Mobile & Analytics with DB2
–Inside engine
• SQL Performance improvement
– (v11 provides 10 – 40%)
• SQL Enhancements (SIMD..)
– & SQL Optimization tools
• Native Stored procedures (zIIP)
• Big Insight support / JSON
– Hybrid platform enrichement
• DB2 Analytic Accelerator
• Java & .Net interfaces (zAAP)
• DRDA support (zIIP)
– Enabeling Business Applications
• Porting Analytics Apps to System z and zLinux
• Rational support

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Database Optimization
– DB2/z hardware utilization
• Compression / Encryption / Floating Point calculations
• zIIP eligible workload / e.g. distributed load through enclaved services
– z Systems Memory and performance enhancements
• DB2 Bufferpool enhancements (more in every version)
• The more memory – the lower CPU usage for queries
• Sysplex & data sharing – data ALWAYS available and unlimited growth available
• DB2 Version 11: 10 40% lower CPU for DB2 workloads
Database New Functionality
– DB2/z near real time data for analytics – run off z platform – inside DB2.
• DB2 Analytics Accelerator
– DB2/z Mobile App enablement
• SQL enhancements (Cube, Rollup, Range etc..) (SMID supported)
• Mobile (JSON), Java (JDBC), Hadoop (BigInsight)
• Native Stored Procedures allows for optimized Business Logic in Mobile Apps
Application Support
– zLinux
• Application Hub inside z – outside zOS
• Sharing zSystems strengths for RAS / allowing openness and flexibility of Linux
– z/OS
• Porting new Analytics Applications to optimize workload for mobile
Primary z Systems & DB2 updates enabling HTAP

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Impressive DB2 11 Performance Results!
Query
Batch
OLTP
XML

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Agenda
– Reporting
• QMF
• Cognos
– Forecasting
• SPSS
• ILOG
Summary

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Degree of Complexity
CompetitiveAdvantage
Standard Reporting
Ad hoc reporting
Query/drill down
Alerts
Forecasting
Simulation
Predictive modeling
Optimization
What exactly is the problem?
How can we achieve the best outcome?
What will happen next?
What will happen if … ?
What if these trends continue?
What actions are needed?
How many, how often, where?
What happened?
Based on: Competing on Analytics, Davenport and Harris, 2007
Reporting
Stochastic Optimization
How can we achieve the best outcome
including the effects of variability?
Descriptive
Prescriptive
Predictive
Business Analytics Adoption Landscape
Increasing prevalence of compute and data intensive parallel algorithms in commercial workloads
driven by real time decision making requirements and industry wide limitations to increasing thread speed
Analytics
Operational
Decision Management
QMF
Algorithmics

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QMF (Query Management Facility) / DataQuant
IBM’s most ‘simple to use’ tool, for SQL driven reports QMF

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QMF

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QMF Websphere for zLinux
QMF
QMF
Websphere

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QMF™ for z/OS 11 goes where you go
Go Mobile!!
QMF for z/OS allows
your users to access
QMF dashboards and
reports from their
tablet devices…
Build once, deploy
everywhere.

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Cognos Analytics on z
Strategy:
- Cognos – largest IBM’s acquisition
Mainframe Business
- Continuous success of large client base on most mature platform, with half
century history
Technology trend:
- Analyze the data where it resides
Cognos 8.4 launch on Linux on System z (2008)
Consistency - since 2008, every Cognos release on Linux, Unix and Windows was
available on Linux on System z
Cognos 8.4.1 on z/OS – Unix System Services (USS) (2011)
Delay due to technical complexity of porting to USS compared to Linux on System z
Cognos 10.2 on USS (2012)
Cognos 10.2.1 on USS with Mobile Release – USS (2013)

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IBM Cognos Business Intelligence
(for Linux on System z & z/OS)
Provides the breadth of BI capabilities required to supports all
users from business critical to tactical to strategic
Provides the qualities of service
required for business critical
analytics
Enables organizations to deliver
BI as a service
Provides access to hadoop data
in place
Reduces the cost of
standardization/consolidation

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IBM Cognos and QMF BI for the Mobile Workforce
Experience insight wherever you are
– Uninterrupted productivity with quick and
easy access to analytics anywhere you go
Interact with information offline or online
– Rich, visual and interactive experience
Confidently and easily deploy Cognos BI on
industry leading form factors
– Single authoring and administrative
environment to deliver secure, relevant, and
reusable content
On the road or in the office –
same great insight.
Simple, reliable, and secure.

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IBM Business Analytics for z Systems
Understand your current state and your
potential state
Monitor results and fine-tune your business
Inform strategy with a view into the future
Cognos BI for zEnteprise
Business intelligence
Business outcomes/benefitsBusiness analytics capabilities
Reporting, analysis, operational & financial planning
and consolidation.
Product profitability solutions across customers,
business lines and channels
Sales Performance Management to improve pay-for-
performance programs and efficiency in incentive
compensation processes
TM1 for zEnterprise
Performance management
SPSS for zEnterprise
Predictive analytics
Predict customer segment and category affinity
Market Basket Analysis to identify the next
best offer for the customer
Overlay browsing history onto purchase history
to profile customers

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Introduction to COGNOS - Core Architecture

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FAST: In-Memory Analysis using Dynamic Cubes
Easier Sizing process
with the Cube Designer Hardware Sizing Guide
(for more details attend the session

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What is predictive analytics?
Predictive Analytics helps connect data
to effective action by drawing reliable
conclusions about current conditions
and future events
Gareth Herschel, Research Director, Gartner
Group
SPSS for zEnterprise
Predictive analytics
Predict customer segment and category affinity
Market Basket Analysis to identify the next
best offer for the customer
Overlay browsing history onto purchase history
to profile customers

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What does a predictive model do?
Cust:ID Balance Monthly savings > 1 Account? Account type Churn
XY6733 1.000 25 Y GT Y
XY7766 50 0 N GX Y
XY6079 5.000.000 500 Y GT N
HH4455 525 100 N GXD N
1. Collect historical information on customers that churned, and customers that stayed
2. Model searches for
common characteristics
3. Model generates rule set
that best predicts churn
Rule Set
Churn is likely, when:
1. xxxxxxxxxxxxxxxxx
2. xxx xxxx
3. xxx xx xxx xxxx
Customers at Risk
1. xxxxxxxxxxxxxxxxx
2. xxx xxxx
3. xxx xx xxx xxxxx
Y
Y
Y
Y Y
Y
Y
Y
Y N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
N
Var A
VarB

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Technique Usage Algorithms
Classification
(or prediction)
• Used to predict group membership (e.g., will
this customer leave?) or a number (e.g., how
many widgets will I sell?)
• Auto Classifiers, Decision
Trees, Logistic, SVM, Time
Series, etc.
Segmentation • Used to segment data points into groups that
are internally similar and externally dissimilar.
• Identify cases that are unusual
• Auto Clustering, K-means,
etc.
• Anomoly detection
Association • Used to find events that occur together or in a
sequence (e.g., market basket)
• APRIORI, Carma,
Sequence
SPSS ‘Technical’ - Data mining techniques
Association ClassificationSegmentation

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Predict at the point of impact!
Level Points
Low Risk > -5
Medium Risk > +1
High Risk > +8
Predictive Analytics
Rules
Structured,
Unstructured, Social
Media. & Business
Intelligence Data
Simulation & Optimization
Scoring
Front-line Rep only sees “Refer” at the point of impact

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Taking Real-Time Scoring to the next level with z System
DB2
for
z/OS
Application
w/latest dataReal-Time Score/
Decision Out
ETLData In
R-T,
min, hr,
wk, mth
Reduced
Networking
In-transaction & In-database scoring
on the same platform
Consolidates Resources
Meet &
Exceed SLA
DB2 for
z/OS Data
Historical Store
Copy
SPSS
Modeler
For Linux on
System z
Scoring
Algorithm
Business
System /
OLTP
Improves the accuracy of
Predictive Analytics by…
Scoring new and relevant
data directly within
transactional applications
Scaling to large data
volumes for use in
building data models
Score 12K transactions per
second in real-time
✔
✔
✔
✔
✔

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SPSS Predictive Analytics
(for Linux on System z)
SPSS Statistics SPSS Modeler Gold
Applies math to decision making and
research for commercial, government,
and academic users
Data mining tool that generates hypotheses
and scoring
Provides text analysis for unstructured data
to model consumer behavior
Includes In-Transaction Scoring with DB2
z/OS: embeds the scoring algorithm directly
within the transactional application

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Business Decisions are Everywhere
We need to add an
eligibility check to
meet the requirements
of the new regulation.
Let’s create a special
promotion for our best
customers.
Can we automate
approvals for this type
of order?
And They Change Frequently
Benefit calculation
Fraud assessment
Eligibility Pricin
g
Underwriting
Configuration
Tax calculation
Billing
Product Selection
Accounting Disposition
Compliance Screening
Documentation Requirements
Commissions / Royalties
Up-sell/Cross-sell offer

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Externalize Decisions from Applications into Rules
Manage decision logic independently from applications
Business Rules
ApplicationApplication
Decision logic
Natural language rules can be easily read
Externalized rules are easy to change
Centralized rules enable reuse and
consistency
Rules written in software code cannot be
read by business people
Hard coded rules are difficult to change
Rules intertwined within applications
cannot be reused by other systems
Without Decision Management With Decision Management
41

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Redefined Application Change Cycle
DeveloperBusiness - IT
Weeks / MonthsDays / Weeks
Functions / Tasks / FlowDecisions / Policies

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IBM Operational Decision Manager v8.0.1
Rule Designer
Event Designer
Rule
Solutions
for Office
Decision Center Versioned Assets
Rule Execution Event Execution Decision Monitoring Connectors
Manage
Decision Server
Console
Design Monitor
Decision Server
Deploy Measure
Visibility
Collaboration
Governance
Define Update
Web Services – API - GUI
DevicesEnterprise
Application
POS BPM CRM
Social
Event Widgets
Space Business Console
Enterprise Console
Access and ControlDecision Artifacts
IBM Operational Decision Manager

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Manage Decisions at the Speed of Business
Major system updates are not required for decision logic changes
requests response
Business Rule Updates
New pricing promotion (monthly)
Updated claims policies (quarterly)
Tightened regulations on trading (annually)
Approve filed claim
Detect fraudulent
trades
Customer searches for a price
2
Decision Logic
Insured members submit claims
Brokers make trades
1
Determine
pricing & bundling
Grow customer base
Increase customer satisfaction
Comply with regulatory changes
Why Decisions Change?
Application
Business Rules

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What does ODM bring to z/OS?
Challenges for
Most z Clients
1. Consolidation,
Isolation, Extension or
Extinction of COBOL
application portfolio
2. Be able to react to
increasing variety and
volume of change
requests
3. Sharing business rules
across platforms &
channels
4. Ensuring seamless
business experience in
migration/ application
evolution
Benefits of the ODM Approach
Cost savings
– Shorter change cycle, without increased business risk
– Rule engine processing is zAAP/zIIP eligible
Improved agility
– Improved Time to Market
– Manage business decisions in natural language
– Decouple development and business decision change
lifecycles
Single version of the Truth
– Consolidated and shared expression of business policy
– Maintainable with a Center of Competency model
Incremental Adoption
– Deploy decision methodology one decision at a time
– Focus on decisions that need to change often & quickly
– Expand adoption of “market validated” decisions

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IBM Decision Server
Leverage a wide range of platforms to meet the varying
needs of enterprise architectures
IBM Decision Center
(Windows, AIX, Linux, Linux on System z, z/OS)
Multiple
z/OS
deployment
options
Windows AIX Linux
(x, p & z) z/OS
Platform support
Repository
IBM Operational Decision Manager

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Agenda
– Reporting
• QMF
• Cognos
– Forecasting
• SPSS
• ILOG
Summary

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z Systems: vision, strategy and technology to fuse transactions and analytics
Streamlined decisioning process
Faster
transactions
Faster transformation
of data
Faster, more accurate
reporting
Faster, more accurate
modeling
Cognos
QMF
(IDAA)
InfoSphere
Repl. Server
Information
Server
CICS, IMS
WebSphere,
SAP, …
Easier integration of other data sources
ODM
BPM
(ILOG)
InfoSphere
BigInsights
InfoSphere
Connector
Faster, more accurate scores
Best of class integrated data life cycle
management for: Generating customer
insights, fighting fraud, preventing
financial crimes, …
SPSS
Cognos

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The z Systems differential
Mainframe continues to be more adaptive and affordable
for mobile workloads
IBM announces new pricing : UP TO 60% reduction of processor increase due
to mobile workloads (no LPAR isolation) and also OTC VUE options
FASTEST
INSTANT Response
Fastest response time,
real-time access to
System of Record,
current data - not old
copy. Acceleration of
queries (up to 2000x)
to meet mobile
demands
TOUGHEST
Data security and
resilence
Modern agile tooling
with pervasive best-
of-breed security,
scalability, RAS
AVAILABLE
data 24/7
Only System z can
handle the
massive spikes
and growth of
mobile workloads

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And don’t forget World of DB2
50
And IDUG, and Insight, and……

Analytics on system z final

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