end-to-end business analytics on system z? yes you can! - bao - db2 ug - eric... · 2020-05-21 ·...

Eric MichielsExecutive IT Architect

Enterprise Computing

IBM BeNeLux - Strategic Initiatives – Enterprise Computing

End-To-End Business Analytics on System z?

Yes You Can!

GSE Joined User Group Meeting

DB2 for z/OS and DB2 for Linux-Unix-Windows

June 21st 2012, 15:45 – 16:45 hrs.


2012 IBM CorporationSlide 2 GSE DB2-IMS Working Group Meeting of 21-Jun-2012

The Questions that are Answered

�Why is Business Analytics so relevant today?

�Why deploying Business Analytics solutions on System z?

�What is the value of a Query Accelerator?

�How can you build a Data Warehouse on System z?

�How can you set up a Business Analytics Cloud with System z?

�Can all Business Analytics flavors be covered by System z?

�How do clients assess their Business Analytics solution on System z?

�How do you feed and maintain your Data Warehouse on System z?

�Does System z allow to run a Dynamic Warehouse ?

�What about the new buzzword “Big Data”?



Business Analytics ... Hot “Again”

� Top priorities for the CIOSource: 2011 Global Midmarket CIO Study

Please visit http://www-935.ibm.com/services/c-suite/cio/study.html

� Top priorities for the CEOSource: 2011 Global CEO Study

Customers want personalization of services and products !



Source Data are increasingly Heterogeneous and Voluminous

Big Data 4 such as data from web logs, RFID, sensor networks, social networks, socialdata, Internet text and documents, Internet search indexing, call detail records,astronomy, atmospheric science, genomics, biogeochemical, biological, interdisciplinaryscientific research, military surveillance, medical records, photography archives, videoarchives, and large-scale e-commerce



Business Analytics provides answers to the 3 KEY QUESTIONS

Dashboard

Operational or Strategic BIQuery & Reporting, OLAP

Exploratory AnalysisStatistics and Data Mining

Predictive Analytics

Extended User Community

Required Capabilities



Who are Successful Leaders? They make Quick Decisions ! (*)

Speed of Decision Taking is a Critical Success Factor

� World events become more interdependent, uncertain, fast-moving, and business-critical

� The speed of execution becomes increasingly important–“Opportunity Windows” become smaller

� More data are being generated, more quickly and more randomly ~ “BIG DATA”

–More users: RFID, Twitter Feeds, Smartphones, ...–Greater network capacity, cheaper storage

� Analytical technology is maturing based on increasing innovation

How to make the BEST decisions?

(*) Likelyhood is 54 % higher - “Insights from the Global CEO Study”, Executive Summary”, IBM GBS

Threath?

Opportunity!



Intuition or Business Analytics?

Decline in homicide rates � 40 %

Sales Increase thanks to Cross-Sell Campaign � 600 %

Cost Savings � € 11 Million

Daily users of IBM Business Analytics � 1000 Client Reps

Increase in cash flow � € 160 Million

Decrease in reporting time on top of Oracle e-Business Suite � 80 %

More Business Analytics � Better Corporate Performance !



Why is System z the Idea Foundation for Business Analytics?

� 60-70% of Operational Data resides on System z

� Copying data from System z to another platform running the Data Warehouse or Data MartsM

– Is costly– Can be inefficient– Takes longer to update– May create data disparities due to challenging data synchronization

• No “single version of the truth” any more”

– Introduces security concerns

� System z offers a fully integrated, holistic solution from Operational Data to Business Analytics

– This is “Business Analytics 2.0” � FAST AND CORRECT DELIVERABLES• New technologies!

� We want ...– To avoid duplication and associated unefficient labor cost !– Reliability, Responsiveness, Security

� But what about ease of use?



Implementing a Business Analytics Solution involves 4 Primary Steps

1. Load data from Operational Data Sources in frequent intervals into a large unified historical data repository known as a Data Warehouse, and potentially Data Marts–Apply Extract, Cleanse, Transform, Load processes

2. Create Reports and Dashboards to answer a variety of what-if questions –Run simple, intermediate or complex queries that can take a few

seconds, minutes, to several hours to run–“OLAP” or “FASMI” capabilities (ROLAP, MOLAP, HOLAP)

3. Use Predictive Analytics to gain insights and convert them to actions –Using data from past, score the likelihood of outcomes for future

events

1

3

4

2



Example of Data Mart Proliferation at Local Government in USA

Data Marts for four departments � significatant costs

1



IBM Internal Study Results of Data Mart Construction Cost Analysis

Pattern

Cost of storage – send file$ 12.33/GB * 1,024 GB

$ 13 K Storage Acquisition Cost $ 123 K

Cost of storage – receive file $ 18/GB * 1,024 GB

$ 18 K

Cost of storage – data mart$ 18/GB * 5,120 GB

$ 92 K

System z Storage Admin$ 5.88/GB/Y * 1,024 GB

$ 6 K Annual Storage Admin Cost$ 61 K

Distributed Storage Admin$ 8.99/GB/Y * 6,144 GB

$ 55 K

System z CPU extract$ 1.38/GB * 1,024 GB * 365

$ 515 K On Premises Network$ 0.0024/GB * 1,024GB * 4 hops * 365

$ 3.6 K Distributed CPU load$ 0.39/GB * 1,024 GB * 365

$ 146 K

System z CPU FTP$ 0.58/GB * 1,024 GB * 365

$ 217 K Off Premises Network$ 0.29/GB * 1,024GB * 2 hops * 365

$ 217 K Distributed CPU FTP$ 0.05/GB * 1,024 GB * 365

$ 17.5 K

System z extract labor$ 4.67/job * 365

$ 1.7 K Annual Transfer Costs$ 1.1 M

365 days in a year

Distributed load labor$ 14.00/job * 365

$ 2.55 K

System z FTP labor$ 2.94/job * 365

$ 1.1 K Data Mart Analysis Costs not included

Multiple copies

1

$ 1.305 M



New Technology is one thing ... but what about Corporate Requirements?

� “Data Analytics 2.0” is quite different–Blade technology–FPGAs - customize logic on the chip–SSDs - fast hard disk–Massive parallelism

� Must be cost-effective–No increase in labor, processes, duplication, facilities M–Reduce complexity

� Must be reliable

� Must be responsive

� Need the latest, accurate data

� Must be secure

� Must be easy to use

zEnterprise can meet all these requirements

1



zEnterprise allows for Holistic Business Analytics!

Operational Data

Additional Data

Additional Data

z/OSLinuxUNIX

Windows

DB2 Oracle MS SQL Server

Extract

Cleanse

Transform

Load

Data Warehouse

Linux

z/VM

InfoSphere Information

Server

Linux

z/VM

InfoSphere Warehouse

z/OS

DB2

New Intelligence

• Reports• Dashboards• Cubes• Analytics

Linux

z/VM

CognosSPSS

Others

Cognos also runs on z/OS

1



DB2 for z/OS is Optimized for Data Warehouse Workloads

�Data Warehouse Workloads typically include a mix of simple, intermediate and complex queries

�DB2 for z/OS Cost Based Optimizer decides upon best execution plan for each query

–Simple queries assigned to a single processing thread–Complex queries may be decomposed into operations that execute in

parallel, exploiting Partitioned Table Spaces• Data for complex queries may be partitioned for parallelism

�Materialized Query Tables (MQT)

�Result: Optimum Throughput

1



DB2 10 for z/OS ~ again a wealth of features supporting the Data Warehouse� Compress on the fly on INSERT

� Auto-statistics

� Access path stability and hints enhancements

� Access path lock-in and fallback

for dynamic SQL

� Automatic checkpoint interval� Automated installation,

configuration & activation of DB2 supplied stored procedures & UDFs

� Data set FlashCopy in COPY & inline copy

� Inline image copies for COPY YES indexes

� UNLOAD from FlashCopy backup� REORG enhancements� Reduce need for reorganizations for

indices� CPU reductions

� Hash access path� Versioned data

� Numerous optimizer enhancements, paging through result sets

� Parallel index update at INSERT� Faster single row retrievals� Inline LOBs� LOB streaming between DDF and

rest of DB2� Faster fetch and insert, lower

virtual storage consumption� DEFINE NO for LOBs and XML

MEMBER CLUSTER for UTS� Query parallelism

enhancements: lifting restrictions

� Dynamic Index ANDingEnhancements

� Option to avoid index entry creation for NULL value

� Index include columns � Buffer pool enhancements � Increased number of active

threads� Reducing latch contention

� Work-file spanned records, in-memory enhancements

� More online schema changes for table spaces, tables and indexes via online REORG

� Online REORG for LOBs � Online add log� Automatically delete CF

structures before/during first DB2 restart

� Allow non-NULL default values for inline LOBs

� Loading and unloading tables with LOBs in stream

� Currently committed locking semantics

� More granular DBA privileges� SQL compatibility� Additional zIIP eligible

workloads

Moving Average

1



z/OS Is Optimized For Data Warehouse Workloads

� Data Warehousing is resource intensive –z196 has more processors , memory and cache than other enterprise

server

� I/O is offloaded to the dedicated I/O sub-system–Extra 14 processoers drive IO–Allows for throughput that is “second to none”

� Parallel Sysplex clustering designed for near linear scaling

� DS8000 delivers high storage bandwidth with caching

� Highest QoS–Given its strategic importance, Business Analytics requires a QoS that is

as important as for operational and business critical workloads• z/OS provides unmatched scalability• z/OS includes systematic Disaster Recovery

� Attractive pricing with IBM Smart Analytics Solution 9700

1



IBM Smart Analytics System 9700 A Comprehensive Package For Business Analytics

� Extend the qualities of service, inherent in the z/OS environment to ensure the availability and security of data

� Hardware and Operating System– IBM zEnterprise z196 technology– IBM System Storage DS8800 Intelligent Disk controller

• Large controller cache and 3 Tier disk offering–z/OS 1.13

� Unique Software–DB2 10 for z/OS–Cognos 10 BI (Linux on System z)– InfoSphere Warehouse (Linux on System z)–SPSS Modeler (Linux on System z)

� Optional Components– IBM DB2 Analytics Accelerator–Solid State drives, integrated within DS8800

• Easy Tier to identify and migrate “hot data” to SSD

1



IBM Smart Analytics 9700 and 9710A comprehensive, strategic, and flexible analytics environment on System z

What does it include:

• zEnterprise Hardware (z196 or z114) : LPAR or Standalone

• Storage: DS8700 with intelligent controller functions and SSA/SATA as optional via special bid

• 3-5 years Maintenance

• Software Stack

• Delivers a PACKAGED SOLUTION into the market place• Leverages IBM industry leading software

• Customized with optional components

• Priced using ”Solution Edition” concept

1



Add IBM DB2 Analytics Accelerator For Even More OptimizationReach an amazing performance!

� What is a IDAA?– A workload-optimized, appliance add-on– Deeply integrated with DB2 for z/OS and

transparent to applications– Significantly speeds up the response time

for a wide variety of intermediate and complex queries

– Drives down the costs of Data Warehousing and Business Analytics

– Application talks to DB2 for z/OS

� Some Characteristics– Powered by Netezza Technology– Massively Parallel Processing– Architecture with data partitioned

across multiple disks, each matched with a CPU

– Incorporates streaming architecture based on Netezza’s patented data filtering using Field Programmable Gate Arrays (FPGAs)

– Tuned for delivering fast query response times for a wide variety of decision workloads

– Uses efficient data filtering by early SQL projections

– Storage integrated into the hardware rack

– Supported on DB2 for z/OS v9 or DB2 for z/OS v10 running on a z114 or z196

1

IDAA Deep AnalyticsOLTP and Transactional Analytics

DB2 z/OSDW OSA-Express3

10 GbE



IDAA Query Execution Process Flow

� IDAA allows for partitioning of data into physical disks and assigning dedicated processors to each disk – throughput scales linearly with partitions

– Large Fact Tables can be partitioned across storage devices – Sample configuration

• 12 Blades: 8 CPU Cores and 1 Disk drive per Blade• 96 disk drives

1



Example of a Typical BI Production Environment Daily Fixed-Set Operational Reports Run Concurrently On A Periodic Schedule

• This is the workload...• ... Let us examine how 3 different BA Infrastructures tackle this

workload, in terms of performance and cost

1



IBM Smart Analytics System 9700 beats ....

Remarks� Results are based on Business Analytics Daily Workload Tests� Performance numbers may vary based on workload profiles

ISAS 9700• 12 GP • 12 zIIP• 128 GB Memory• DS8800 with 600 GB * 4

2 DBMS NodesEach node:• 2 x Quad Core CPU• 72 GB Memory

3 Storage DevicesEach node:• 2 x Quad Core CPU• 24 GB Memory• 4 * 88 GB

1



IBM DB2 Analytics Accelerator makes a great Analytics Solution Even Better

2 DBMS Nodes• 2 Quad Core CPU• Memory 48 GB

8 Blades 64 Bit Linux• Each 16 GB Memory• 16 Cores• 1 TB data

Remarks� ISAS + IDAA performance estimated from ISAS running simple reports, and NZ

TF12 running intermediate + complex reports

ISAS 9700• 5 GP • 5 zIIP• 128 GB Memory• DS8800 with 600 GB * 4

ISAS 9700 + IDAA TF12

1

� Performance Elapsed Time is 5 times better

� Price/Performance is 4 times better



Customers Are Excited About Business Analytics On zEnterpriseOnly a few examples 4

DB2 Analytics Accelerator: “We had this up and running in days with queries that ran over 1000 times faster”

DB2 Analytics Accelerator: “We expect ROI in less than 4 months”

Cognos BI for System z: “We didn’t have to justify a higher cost for putting this on System z, it was cheaper!”

Analyst Claudia Imhoff: “The industry pendulum is swinging towards centralization and there is no better platform than the zEnterprise”

1



IDAA Anonymised Results

� Production ready with 1 person in 2

days

� Table Acceleration Setup in 2 Hours

– DB2 “Add Accelerator”– Choose a Table for “Acceleration”– Load the Table (DB2 Loads Data to

the Accelerator)– Knowledge Transfer– Query Comparisons

1

• Initial Load Performance• 400 GB Loaded in 29

Minutes• 570 Million Rows• Loaded 800 GB to 1.3 TB

per hour• Extreme Query Acceleration

• 1908x faster• CPU Utilization Reduction

• Up to 35%



The easy road to a DB2 for z/OS Data Warehouse with InfoSphere Warehouse

26

• Low latency through regular extracts of new data with InfoSphere Warehouse SQW• Keep your data highly available, reliable, secure, and compliant with DB2 for z/OS • Reduce impact on transactional data and systems through the use of InfoSphere

Warehouse Cubing Services

1. Model your data for OLAP access using the InfoSphereWarehouse Design Studio

2. Populate your star schema using InfoSphere Warehouse SQW Scripts

3. Build one or more Cube structures using the InfoSphereWarehouse Design Studio

4. Access data through Excel or Cognos MDX queries

InfoSphere Warehouse Design StudioCognos

Excel

System z Environment Improved with InfoSphere Warehouse

z/OS Linux for System z

OLTP DB2 DWH DB2

SQW

MDX Queries

Cubing Services

1

2

3

4

2



InfoSphere DataStage on Linux on System z

� Accelerate development of integration processes

� Delivers hundreds of pre-built re-usable transformation components and routines

� Delivers a scalable platform to meet both batch and real-time demands

� Collaborative, reusable and productive metadata driven development

� Support for complex transformations across heterogeneous systems

� Massively scalablearchitecture and performance

Requirements

Benefits

Transform and aggregate any volume of information in batch or real time through visually designed logic

CDC

1 4

5

2

DataStage

databasedatabase

SourceCDC Transaction Stage

Database Connector Stage

CDC

DataStage

Target

1

3

5

2

2

Design logic once

Run and scale anywherePack for “Data Masking”

2



For Real Time Business Analytics,Incremental Updates are Indispensible

InfoSphere• Replication Server• Change Data Capture

2



IBM InfoSphere QualityStage on Linux on System z

� Specialized data quality functions seamlessly integrated with InfoSphere DataStage� Visual tools for defining complex matching and survivorship logic� Ensures clean, standardized, de-duplicated information� Enables a single version of the truth

InfoSphere QualityStage™

Un-cleansedSource Data

CleansedDataPhase 1 Phase 2 Phase 3 Phase 4

Flow� Phase 1: Investigate your data� Phase 2: Standardize your data

SETID SSN Name Address City State Zip Code

1 NULL Jerome David Salinger Holden Caulfield Hwy Agerstown PA 19102

1 NULL J. David Salinger 51 Holden Caulfield Hwy Agerstown PA 19102-1919

1 123-45-6789 J.D. Salinger Holden Caulfield Hwy Agerstown PA 19102

SETID SSN Name Address City State Zip Code

1 123-45-6789 Jerome David Salinger 51 Holden Caulfield Hwy Agerstown PA 19102-1919

Survivorship Output used to update the Master Data

Input Data

Flow� Phase 3: Match your data� Phase 4: Maintain your matched data

2



Create Reports and Dashboards using Cognos

� People-centric– Server based business analytics accessed via browser with

thousands of users and not hundreds of users– Consistent user interface for different analytic activities –

extremely consumable– Reuse new intelligence assets– Built-in collaboration and social networking– Threaded discussions, activities, and notifications

� Easy to deploy and manage– Implemented in Java, runs on WebSphere Application Server

or another Java EE Application Server– Scales up and out across heterogeneous hardware and

operating systems– Runs on Linux on System z

� You need to create a meta model to hide database naming and tansform in business terms

– Nice: common meta model !

� Query Studio, GIS, Pivoting, Report Studio, PowerCubes, are integrated functions

3



IBM Cognos Provides a Unified Workspace

� All activities from one place, without jumping to different interfaces• Dashboards for summary overview

• Reports for tracking progress

• Ad hoc queries and drill down for analysis and what if scenarios

• Statistics and predictive analysis

� Progressive interaction – interact and analyze information based on role

� Form decision networks for collaborative business analytics

� Lotus collaboration technolgies are integrated into Cognos

� Serves users from different LOBs and with different interest areas

3

Cognos BI High Level Architecture



Reuse Prior Assets In New Deliverables

� Author once, consume anywhere–No export/import needed

� All analytic assets share a common metadata model and a common multilingual report specification

� Publishing is possible in multiple formats

� Ensures consistent information and enables reuse across platform functions

� You have options to bring together different visusalizations in one web based interface

–Adobe Flex technolgy used

3



Miami Dade County Runs Cognos on Linux on System z

Requirements� Demand for BI has really taken off

– New Federal reporting

requirements

– Every new system, every new solution, every new application is having a business intelligence

component

� Multiple Cognos BI deployments� Wanted an enterprise BI

standardized solution, but– Needed higher capacity – grow

from approximately 400 to 1000 users

– Do more with less - less researchers, less software, less hardware, same staff

– Had available IFL’s on System z

Results� 11 days to move from distributed to System z

deployment model for Cognos BI– Quickly and easily meet new requirements– High QoS on short term

� Consolidate multiple BI deployments on to a single platform

� Single point for BI administration� Consolidate multiple disparate data sources� Ensure 99.999% availability� Offer a complete disaster recovery plan� Additional green savings

3



Analytics Cloud based on Cognos on Linux on System z

Sample Deployment

3



SPSS enables customers to Predict Future Events and drive better Business Outcomes

� Sample Questions

• What is the profile of my most profitable clients? Which campaign should I deploy for up-selling?

�CLUSTERING

• Will this new prospect be profitable for my insurance business, or will he generate a lot of claims?

�VALUE PREDICTION

• Which products should I bundle or not bundle in order to maximize revenue and profits?

�ASSOCIATIONS

• What is the probable acquisition sequence of services for this type of client?

�SEQUENTIAL PATTERN

• Are there Buying Patterns that frequently occur and can we couple them to the demographic

profiles of our clients?

�SIMILAR TIME SEQUENCE

• Given the blood pressure and the Cholesterol values, is this patient candidate for a desease?

�CLASSIFICATION

� Solution: SPSS �� “Statistical Package for Social Sciences”

– Key role in creating the Predictive Analytics market

– Acquired by IBM October 2009

– SPSS has the most customers in the most industries

– 250,000 customers

– Over 95% of the Fortune 1000

4



The Predictive Analytics Methodology

Recommend the mostappropriate actionto take

Store new data on customers, events, etc. for continuous improvement

Predictive Analytics

Analyze data toprovide insight andpredict the future

Capture

Predict

Act� Identify Fraud� Improve customer retention�Grow share of wallet�Minimize risk�Increase customer satisfaction

36

Prospects

Customers

Traffic

Claims Weather

Material

36

Data Collection delivers an accurate view of customer

attitudes and opinions

Predictive capabilities bring repeatability to ongoing decision making, and drive confidence

in your results and decisions

Unique deployment technologies and methodologies maximize the impact of

analytics in your operation

StatisticsText

MiningData

Mining

4



SPSS Predictive Analytics Software available on Linux for System z(3 out of 4 Categories)

37

Data CollectionDelivers accurate view of customer attitudes & opinions

• IBM SPSS Data Collection

StatisticsDrives confidence in your results & decisions

• IBM SPSS Statistics

ModelingBrings repeatability to ongoing decision making

• IBM SPSS Modeler

• IBM SPSS Text Analytics

DeploymentMaximizes the impact of analytics in your operation

• IBM SPSS Decision Management

• IBM SPSS Collaboration & Deployment Services

4



IBM SPSS Modeler and Text Analytics

� High-performance data mining

algorithms and workbench – Set of mining algorithms that provide

insight and prediction– Enables the discovery of key insights,

patterns and trends in data that can be used to optimize business decisions

� Benefits– Maximize Analyst Productivity

• Easy to learn• Don’t have to be a programmer or a trained

analyst

– Automation drives rapid ROI• Automatically create, evaluate and deploy

predictive models• Automate data preparation

– Performance and scalability• Best in class database pushback for data

transformations and data mining algorithms• Multithreading, clustering and use of

embedded algorithms

Brings repeatability to ongoing decision making

4

� Uses natural language processing heuristic rules and statistical techniques to reveal conceptual meaning in text

– Makes unstructured qualitative data more quantifiable, enabling the discovery of key insights from sources such as survey responses, documents, emails, call center notes, web pages, blogs, forumsand more

� Benefits– Broaden the Perspective– Enrich narratives with numbers for deep

understanding



Predictive Analytics and Business Rules Synergies

� Predictive Analytics � implicit patterns based on historical data and statistical analysis

� Business Rules � explicit patterns based on internal knowledge (e.g. best practices), regulations, and policies

� This combination allows for “Operational Decision Management”– Typically leverages a combination of these technologies:

� Business Rules Management � Business Event Processing� Business Process ManagementAND� Predictive Analytics � Business Intelligence & Performance Management

39

4



Acceptabl

e

ris

k?

Aggregate score

& risk assessment (BRMS)

Refusal LetterPricing

(BRMS)

Internal

Predictive Risk

Score)

YesNo

Credit Bureau Risk

Score(s)

Eligible?

Eligibility

Determination (BRMS)

Yes

No

How are our customers using Business Rules together with Predictive Models?At design time

• Using Predictive Models to improve Business Rules

• Updating Business Rules with Model results

• Using Predictive Models to create new explicit Business Rule artifacts

• Creating Business Rules from Models

At run time

• Using Business Rules to determine which Predictive Model to apply

• Using Business Rules to reference Predictive Scores at runtime

• BPM/SOA Orchestration of standalone decision and scoring services

4



End-To-End Business Analytics on zEnterprise!

InfoSphereInformation

Server

OLTPdata

DB2 for z/OS DWH

Cognos BIfor Linux on System zD

SPSS on Linux on System z

Serving Up Consolidated Enterprise BI

Complete ETLSolution

The Enterprise Data Warehouse

InfoSphere Warehouse Cubing

Services

InfoSphere Warehouse -Data Warehouse

Modeling

Source Systems :

DB2IMS

VSAMNon IBM

Industry Data Models Available

DB2 for z/OS Tools DB2 for z/OS Tools

IMS Tools

IBM DB2 Analytics Accelerator

z/OS LPARProduction Data

Linux IFLTooling

z/OS LPARWarehouse Data

Linux IFLTooling



zEnterprise is an excellent platform for Business Analytics!

� Operational and Warehouse Data co-located on z196 or z114 for optimal performance

� Exploitation of IBM DB2 Analytics Accelerator for medium-complex and highly-complex queries

� Cognos supports a common metadata model and report specification, and provides 100% browser-based access

� SPSS predictive analytics provides actionable insights versus “hindsight”

� Systematic Disaster Recovery and Backup Strategies

� “Data Base Tuning for Performance” is an established discipline

� Qualities of Service

� Competitive Pricing



Global Name

Recognition

Warehouse

Cognos

BI

InfoSphere Information

Server

ETL

Data Quality

Dynamic WarehouseThe Integrated Stack for System z

InfoSphereIndustry Models

InfoSphereWarehouse

Cubing

InfoSphereMDM Server

Information

Services

Director

Data Synchronization

Replication

Server

Classic Event

Publisher

Classic

FederationFederation Change Data

CaptureOperational Source SystemsStructured/ Unstructured Data

Operational Applications

GlobalName

Recognition

Master Data

IBM DB2

Analytics

Accelerator

Smart Analytics System 9600

SPSS



Because Big Data matterM

InfoSphere Big Data PlatformAllows organizations to extract insight from an immense Volume, Variety and Velocity of data, in context, beyond what was previously possible

� At the Swedish Institute of Space Physics, performed analytics on at least 6 gigabytes per second or 21,600 gigabytes per hour

� Financial services customer managed 5 million stock message per second, 150 microsecond latency

Solutions

InfoSphere BigInsights

InfoSphere Streams

Streaming Analytics

� Analyze streaming data� Analytics for text,

structured data, statistics, audio, video

� Ultra-low latency

performance

� RDBMS, Data Warehouse integration

Internet Scale Analytics

� Hadoop-based � User visualization� Development environment� Text analytics

� Scale to significant data

volume

� RDBMS, Data Warehouse integration



IBM Business Analytics & Data Warehousing on System z Product Portfolio

Business Intelligence� Cognos Business Intelligence for Linux on

System z� Cognos Business Intelligence for z/OS

Predictive Analytics� IBM SPSS Statistics:� IBM SPSS Modeler:� IBM SPSS Collaboration and Deployment

Services� IBM SPSS Decision Management

Extract-Cleanse-Transform-Load and

Metadata ManagementIBM Information Server family� InfoSphere DataStage for Linux on System z� InfoSphere Information Analyzer for Linux on

System z� InfoSphere QualityStage for Linux on System z� InfoSphere Metadata Server for Linux on System z� IBM Metadata Workbench for Linux on System z� InfoSphere Business Glossary for Linux on

System z� InfoSphere Information Services Director for Linux

on System z� Replication Server, Change Data Capture

Data Warehousing� DB2 for z/OS VUE (Value Unit Edition)� InfoSphere Warehouse for Linux on System z

– Tooling, SQW, Cubing Services� DB2 Analytics Accelerator� DB2 for z/OS Tools

Infrastructure Platform� z196� z114� zBX

Flexible Deployment Options� IBM Smart Analytics System 9700� IBM Smart Analytics System 9610� IBM Smart Analytics Cloud



IBM Total Solution Event for System zSeptember 18 - 20, 2012 – IBM Forum Brussels

Track 1 zEnterprise for IT Managers and Executives

Track 2 zEnterprise for IT Architects

Track 3 New Technologies on zEnterprise

Track 4 Maximize Scalability and Flexibility with Linux and z/VM on System z / z/VSE Update

Track 5 Cloud Computing with zEnterprise

Track 6 Integrated Management and Monitoring of zEnterprise

Track 7 Managing and exploiting Enterprise Data and Information

Track 8 Exploiting Modern Application Architectures on zEnterprise

Track 9 Increasing Productivity and Time to Market with Application Development Solutions for zEnterprise

Track 10 DB2 on z/OS Update

Track 11 IMS Update

Track 12 CICS Update

More than 60 sessions during 3 days brought to you by ITSO and worldwide experts. Don’t miss this free of charge event and spread the news!

https://www-950.ibm.com/events/wwe/grp/grp021.nsf/v16_agenda?openform&seminar=AZCPQPES&locale=en_BE



� IBM zEnterprise landing page: http://www.ibm.com/systems/z/hardware/zenterprise/index.html

� IBM zEnterprise 114 (z114): http://www.ibm.com/systems/z/hardware/zenterprise/z114.html� IBM zEnterprise Events Landing Page: http://www.ibm.com/systems/breakthrough� IBM software for zEnterprise: http://www.ibm.com/software/os/systemz/announcements � IBM System Storage: http://www.ibm.com/systems/storage/product/z.html� IBM Global Financing: http://www.ibm.com/financing/us/lifecycle/acquire/zenterprise/� IBM Services for zEnterprise: http://www.ibm.com/services/us/gts/zenterprise/index.html� IBM zEnterprise / System z Redbooks Portal: http://www.redbooks.ibm.com/portals/systemz

� Proof-Of-Concept?� Life Demonstration?� Sizing?� TCO Study? � Fit For Purpose Workshop?� Customer visit or call?

47

More information on ThalerMore Information Sources

[email protected]



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Merci

Bedankt

Gracias!

Obrigado

Danke

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end-to-end business analytics on system z? yes you can! - bao - db2 ug - eric... · 2020-05-21 ·...

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