Best Practices for Managing JD Edwards Data: Preparing for Upgrades, Migrations and more

Sambasivam Sampathnathan – World Wide Product Manager IBM Software Group

08/16/2011

Today’s Discussion

•  What  drives  upgrades  today?  •  Data  management  strategies  for  your  upgrade  project  •  Archiving  and  Upgrades  

–  Concepts  &  Benefits  –  Key  Requirements  

•  Managing  test  data  •  Client  Success  Story  •  QuesEons  &  Answers

What Drives Upgrades Today

•  Maximize  value  from  exisEng  investments  in  current  economic  condiEons:  Fusion  apps  sEll  under  development  

•  Changing  business  processes/requirements  •  ApplicaEon  instance  consolidaEon  •  Technology  –  Out  with  the  old,  in  with  the  new  

–  New  features;  industry  compliance  –  Obsolete  hardware,  middleware  &  database  plaSorms  

•  Vendor-­‐imposed  upgrade  deadlines  

Common Drivers of Data Growth

•  OrganizaEon  growth  •  Reduce  IT  Cost  •  Data  retenEon  compliance  •  Too  much  of  everything  

–  Keeping  data  “always  available”  •  Data  mulEplier  effect  

•  Use database partitioning

•  Use database vendor compression

•  Buy more Storage & CPU hardware

Hardware Capacity

Performance

Dat

abas

e Si

ze

*Source: Forrester Research, Database Archiving Remains An Important Part Of Enterprise DBMS Strategy, Q3 2007

Forrester estimates that, on average, data repositories for large applications grow by 50% annually (structured data).

How are Organizations Responding to Data Growth?

•  Segregate  historical  enterprise  applicaEon  data  by  age,  status,  event  or  other  criteria  

•  Copy  historical  records  to  a  secure  archive  •  Delete  transacEon  details  from  producEon  system  •  Retain  access  to  informaEon  for  query,  reporEng,  customer  

service,  audit  and  discovery  requests  

Current

Production

Historical Archive

Archive

Historical Data

Reference Data

What is Archiving?

•  Streamline  the  upgrade  project  –  Reduce  downEme  during  conversion  by  50%  or  more  –  Improve  applicaEon  performance  from  old  version  to  new  version  by  reducing  OLTP  workload  

•  Maintain  a  superior  ownership  experience  –  ongoing    –  Reduce  backup  and  disaster  recovery  Eme  by  hours  –  Lower  database  maintenance  Eme  for  tasks  like  reorganizaEons,  refreshes,  clones  

–  Support  “compliance  readiness”  –  Ensure  consistent  performance  to  Service  Level  objecEves  –  Reduce  cost  of  storage  and  overall  TCO  

What are the Benefits of Archiving?

•  What  data  should  I  be  saving,  for  how  long  and  for  what  reasons?  

•  What  data  should  I  be  deleEng?  •  How  am  I  going  to  find  the  data  when  I  need  it?  •  What  do  I  do  with  the  data  when  I  no  longer  need  it?  •  What  is  the  cost/benefit  analysis  to  support  an  archiving  

soluEon  acquisiEon?  •  What  is  the  most  appropriate  soluEon  to  meet  my  archiving  

needs?  

Data Archive Strategy: Questions to Consider

1   ApplicaEon  Intelligent   • JD  Edwards  EnterpriseOne  

2   Take  the  right  data  out  • Complete  Business  Object  • Apply  Func>onal  Condi>on  Checks  • Accommodate  Unique  Business  Requirements  

3   Store  it  where  you  want  

• Support  &  automate  data  reten>on  policies  as  per  ILM  business  requirements  

• Mul>ple  formats  –  DBMS,  File  

4   Access  archived  data  when  &  how  you  want  

• Na>ve  applica>on  access  • Applica>on  independent  access  

Archiving Solution: 4 Key Requirements

•  Complete  Business  Object  –  Includes  pre-­‐defined  related  J.D.  

Edwards  tables  –  TransacEon  data  as  well  as  

contextual  and  reference  data  •  Integrity  Checks  •  Custom  columns  are  recognized  

automaEcally  •  AddiEonal  custom  tables  can  be  

added  visually  •  SelecEon  criteria  or  integrity  

checks  may  be  applied  to  any  column:  AutomaEcally  applied  to  all  related  rows.  

1 Application Intelligent

Archive Solution

•  Access Definitions •  Complete Business Object •  Business Rules •  Validations

1 - 2 Years Current Data

Production Database

Extract

2 Archive the Right Set of Data

•  Represents application data record – payment, invoice, customer –  Referentially-intact subset of data across related

tables and applications; includes metadata •  Provides “historical reference snapshot” of business

activity •  Federated object support across enterprise data

stores

2 Archiving a Complete Business Object

Table captured as reference table during archive process

Records in table removed from database during archive process

All Records included

AAI’s

F0012

General Ledger

F0911

Business Unit Master (closed jobs)

F0006 Fiscal Data Pattern

F0008

Ledger Type Master

F0025

Address Book

F0101 Batch Control

F0011

Tax Area

F4008

Account Master

F0901 Chart of Accounts

F0909

Account Balances

F0902

Tax Table

F0018 GL Tag

F0911T

Company Master

F0010

•  Represents application data record – payment, invoice, customer –  Referentially-intact subset of data across related tables and

applications; includes metadata •  Provides “historical reference snapshot” of business activity •  Federated object support across enterprise data stores

2 Complete Business Object - Example

•  Both  invoice  closed  date  and  receipt  GL  Date  must  fall  within  the  specified  period  

•  The  invoice  and  receipt  are  posted  and  all  corresponding  G/L  entries  are  posted  

•  All  the  invoices  must  be  paid  and  the  payment  status  must  be  equal  to  ‘P’  

•  The  domesEc  and  foreign  open  amounts  both  must  be  equal  to  zero  

•  Recurrent  invoices  (doc.  type  RR)  are  only  archived  if  the  number  of  installments  is  blank  

2 Business Rules & Validations Example

3 Compressed

Archives

2 -

4 Y

ea

rs

Activ

e/Hist

orica

l Onl

ine

XML

Archive Database

Non DBMS Retention Platform

ATA File Server SATA / FATA disk

4 -

6 Y

ea

rs

On/N

ear-L

ine A

rchi

ve Off-line Retention Platform CD,Tape,Optical, WORM HP StorageWorks™, IBM TSM NetApp NearStore® SnapLock™, IBM Information Archive/TSM EMC Centera™. 6

+ Y

ea

rs

Off-L

ine A

rchi

ve

Archive Solution

•  Access Definitions •  Complete Business

Object •  Business Rules •  Validations

1 - 2 Years Current Data

Production Database

Extract

Store It Where you Want

FuncEonal  Usage  /  Access  Requirements  Over  Time  

Business  Object  

Frequent,  ApplicaEon-­‐

Based  Access  

Infrequent,  Ad-­‐Hoc,  

Query-­‐based  Access      (Self-­‐

Help)  

ExcepEon-­‐based,  ApplicaEon-­‐Independent  

Access    (24-­‐hour  IT  response)  

Complete  DeleEon    (Dictates  storage  

planning)  

Journals  (GL)   Current  –  2Y   Years  3  –  5   Years  6  -­‐  10   Year  11  

Invoices  (AP)   Current  –  2Y   Years  3  –  5   Years  6  -­‐  10   Year  11  

TransacEons  (AR)   Current  –  2Y   Years  3  –  5   Years  6  -­‐  10   Year  11  

Purch.  Orders  (PO)   Current  Year   Year  2   Years  3  -­‐  10   Year  11  

Sales  Order  (SO)   Current  –  2Y   Years  3  –  5   Years  6  -­‐  10   Year  11  

Fixed  Assets  (FA)   Current  Year   Year  2   Years  3  -­‐  10   Year  11  

3 Support ILM Business Requirement

4 Compressed

Archives

2 -

4 Y

ea

rs

Activ

e/Hist

orica

l Onl

ine

XML

Archive Database

Non DBMS Retention Platform

ATA File Server EMC Centera™, DR550, Etc.

4 -

6 Y

ea

rs

On/N

ear-L

ine A

rchi

ve

Off-line Retention Platform CD,Tape,Optical, WORM HP StorageWorks™, IBM TSM NetApp NearStore® SnapLock™, IBM Total Storage® solutions (including the DR550) EMC Centera™.

6+ Y

ea

rs

Off-L

ine A

rchi

ve

Archive Solution

•  Access Definitions •  Complete Business

Object •  Business Rules •  Validations

Extract

U N I V E R S A L A C C E S S

Restore

1 - 2 Years

Current Data

Production Database

Additional Options

ODBC / JDBC

XML

SQL

Excel / Access

Native Application Access

IBM Mashups

Access Archived Data

Archive

Reporting Solution Options

• Report Writers: •  Cognos •  Business Objects •  Discoverer

• Mashup Center • Access • Any SQL-based tool set • Browser • Java Application

•  Open & independent •  No training of end users or audit staff •  Leverage existing tools and skills •  OLTP not required

4 Access Archived Data Thru Reporting Tools

1.  Archive  before  an  Upgrade  –  Reduces  amount  of  data  to  convert  during  producEon  cutover  –  Reduces  downEme  during  upgrade  

2.  Archive  in  Parallel  with  an  Upgrade  –  Combines  common  technical  and  funcEonal  tasks  to  save  overall  elapsed  Eme    

•  Technical  Tasks:    Validate  individual  steps  (such  as  moving  query  tables  forward),  validaEng  new  technical  environment,  performance  tesEng  

•  FuncEonal/Business  Tasks:  Reconciling  “before”  &  “aner”  results,  regression  tesEng  on  key  business  processes  (such  as  payroll  processing  or  financial  close)  

Where Does Archiving Fit?

Application

Older Version Upgraded Version

Archives

Universal Access to Application Data

ODBC / JDBC XML Report Writer Application

Upgrade Project

Application

Current Data

Archives

Current Data Application

Data Archive

1. Archive Before Upgrade

Application

Older Version Upgraded Version

Universal Access to Application Data

ODBC / JDBC XML Report Writer Application

Upgrade Project

Application

Current Data

Archives

Application Data

Archive

Archive Planning

2. Archive & Upgrade Projects in Parallel

Data Warehouses

The Actual Data Burden = Size of all production database + all replicated clones

According to Forrester, on average, data repositories for large applications grows by 50% annually (structured data)!

1 TB Back-up

1 TB Disaster Recovery

Back- up

Disaster Recovery

Master Data

Back-up

Disaster Recovery

1 TB ERP/CRM Application

Test

Dev

UA

1 TB

Dev

Test

UA

Dev

Test

UA

Data Multiplier Effect

#1 - Clone Production

Wait

Manual examination: Right data?

What Changed? Correct results?

Unintended Result? Someone else modify?

Clone Production

Request for Copy

Production Database

Copy

Production Database

Copy

After

Changes

#2 – Write SQL

Share test database with everyone else

•  RI Accuracy? •  Right Data?

Expensive, Dedicated Staff, Ongoing Responsibility

Changes

•  Complex •  Subject to Change

Write SQL Extract

Extract After

Creation of Test Environment: Current Practices

100 GB

25 GB

50 GB

• Create targeted, right-sized test environments

• Substitute sensitive data with fictionalized yet contextually accurate data

• Easily refresh, reset and maintain test environments

• Compare data to pinpoint and resolve application defects faster

• Accelerate release schedules

Production or Production Clone

25 GB

2TB

Development

Unit Test

Training Integration Test

Extract Relational subset

Load / Mask Insert / Update Compare

Effective Test Data Management

“When performing the development upgrade, it is important to leverage a representative subset of production data instead of an exact copy; this is because the development environment usually has less capacity in both memory and hard drive space than the test and production environments. Limiting the size of the conversion files during the development upgrade will better ensure that the processes will complete in a timely manner.”

Tip #27—Test with a Representative Subset of Production Data

Testing Best Practices - Oracle

•  62%  of  companies  surveyed  use  actual  customer  data  instead  of  disguised  data  to  test  applicaEons  during  the  development  process  –  50%  of  respondents  have  no  way  of  knowing  if  the  data  used  in  tesEng  had  been  compromised.  

•  52%  of  respondents  outsourced  applicaEon  tesEng  –  49%  shared  live  data  

Source: The Ponemon Institute. The Insecurity of Test Data: The Unseen Crisis

Data in Test & Development Environments

•  Also  known  as:  data  de-­‐idenEficaEon,  depersonalizaEon,  desensiEzaEon,  obfuscaEon,  data  scrubbing  

•  Technology  that  helps  conceal  real  data  •  Scrambles  data  to  create  new,  legible  data    •  Retains  the  data's  properEes,  such  as  its  width,  type  and  format  •  Common  data  masking  algorithms  include  random,  substring,  

concatenaEon,  date  aging  •  Used  in  non-­‐producEon  environments  as  a  Best  PracEce  to  

protect  sensiEve  data  

Mask Data in Non-Production Environments

•  Mask  or  de-­‐idenEfy  sensiEve  data  elements  that  could  be  used  to  idenEfy  an  individual  

•  Ensure  masked  data  is  contextually  appropriate  to  the  data  it  replaced,  so  as  not  to  impede  tesEng  

•  Data  is  realisEc  but  ficEonal  •  Masked  data  is  within  permissible  range  of  values  

•  Support  referenEal  integrity  of  the  masked  data  elements  to  prevent  errors  in  tesEng    

Personal identifiable information is masked with realistic but fictional data for testing & development purposes.

JASON MICHAELS ROBERT SMITH

De-identify Data Without Impacting Dev & Test

•  Redundant  systems  acquired  via  mergers  and  acquisiEons  

•  Line  of  business  divested  •  Legacy  technologies  not  compaEble  with  current    IT  direcEon  

•  Required  technical  skills  or  applicaEon  knowledge  no  longer  available  

•  Budget  pressures  –  do  more  with  less!  

Why Retire or Consolidate Applications

•  Consolidate  mulEple  applicaEons  into  a  single  instance  and  reEre  unused  applicaEons  –  Move  from  home  grown  to  packaged  system  –  Consolidate  similar  systems  due  to  mergers  and  acquisiEons  

•  Consolidate  an  independent  business  process  with  others  –  Move  automaEon  capabiliEes  into  a  single  system  and  reEre  

independent  applicaEon  •  Move  applicaEon  from  an  old  to  new  architecture    

–  Not  all  data  is  relevant  for  the  move,  but  it  must  be  retained  •  Shut  down  legacy  system  without  a  replacement  

In  almost  ALL  cases,  access  to  legacy  data  MUST  be  retained  while  the  applica<on  and  database  are  eliminated  

Retire Unused Legacy Applications

Benefits  –  Reduce  IT  infrastructure  costs  (hardware,  sonware,  labor  costs)  

–  Reduce  infrastructure  complexity  (eliminate  confusion)  

–  Reclaim  assets    

Archiving allows you to move the data needed while maintaining access to the original data in its business-object form without the original application.

Retire the Application, Not the Data

•  Proven  leader  in  Integrated  Data  Management  (IDM):  –  Manage  and  Control  Data  Growth  –  Data  RetenEon,  Compliance  &  Discovery  –  Speed  ApplicaEon  Delivery  &  Quality  with  Test  Data  

Management  –  Speed  ApplicaEon  Upgrades  &  MigraEons  –  ApplicaEon  ReErement  –  Improve  Storage  Management  –  ILM  –  Improve  ApplicaEon    Performance  and  SLAs  

•  Solving  complex  data  management  issues  since  1989  

•  Global  company:  2500  clients;  50%  of  Fortune  500  •  Recognized  by  Gartner,  IDC,  META  as  EDM  

industry  leader  with  46%  market  share.  

About IBM Optim

•  Op>m  Data  Growth  Solu>on  (Archiving)  –  Improve  performance  –  Control  data  growth,  save  storage  –  Support  retenEon  compliance  –  Enable  applicaEon  reErement  –  Streamline  upgrades  

•  Op>m  Test  Data  Management  Solu>on  –  Create  targeted,  right  sized  test  

environments    –  Improve  applicaEon  quality  –  Speed  iteraEve  tesEng  processes  

•  Op>m  Data  Privacy  Solu>on  –  Mask  confidenEal  data  –  Comply  with  privacy  policies  

IBM Optim™ Solutions

Discovery

Data Growth Data Privacy Test Data Management Application Retirement

Organization environments are diverse, yet interrelated; therefore what you use to manage the data MUST support across your environment

IBM Optim: Enterprise Architecture

•  IBM InfoSphere Optim Data Growth Solution

§  Leveraging their Oracle packaged-application for manufacturing, shipping and finance. Since installing in 2003, the system has grown tremendously, from 300 GB to more than 1 TB of information.

§  Calculated it would take 5 to 7 business days to perform the upgrade and data conversion. That amount of downtime for a business critical application would be unacceptable.

Challenge Business Benefits §  The upgrade and data conversion was

completed over a 3-day weekend, eliminating the need for downtime during business hours.

§  Archived data is still accessible to functional users via an archive database, so there was minimal training needed.

§  Archived data was stored on “tier 2” storage. This provided an estimated annual savings of $75,000-$80,000 in storage costs.

§  Archiving project was completed 3 weeks ahead of schedule, allowing for additional preparation time for the upgrade project itself.

Solution “Without IBM Optim software, it would have taken us nearly twice as long to upgrade our ERP application, forcing us to shut down manufacturing. Instead, we completed the process in one three-day weekend without any business interruption.”

Success Story: Application Upgrade & Cost

Objective: Minimize business disruption during JD Edwards upgrade and improve system performance to support business operations

Solution: Optim Data Growth Solution for JD Edwards EnterpriseOne Reduced the volume of audit trail & workflow activity by 63%, shortening data conversion window and improving system performance.

Objective: Need to reduce projected system downtime for JD Edwards upgrade from 8 days to 3 days to avoid business disruption

Solution: Optim Data Growth Solution for JD Edwards EnterpriseOne Completed upgrade and data conversion over a 3-day weekend, eliminating downtime during business hours; stored archive data on “tier 2” storage, saving $80K annually in storage costs

Objective: Need to reduce the database size of enterprise system, and manage the ongoing data growth for financial and supply chain information

Solution: Optim Data Growth Solution for JD Edwards EnterpriseOne Reduced the database size & implemented data growth strategy, creating a 50% reduction in system maintenance and 300% improvement in query times

Objective: Minimize business disruption during JD Edwards upgrade and control 25% annual data growth & corresponding storage costs

Solution: Optim Data Growth Solution for JD Edwards EnterpriseOne Attained a 50% reduction in their needed future purchases of data storage, streamlined the data migration process during the upgrade project, and reduced the time needed for ongoing maintenance

Other Examples

Featured List of Optim JD Edwards Customers

Enterprise Customers

•  Define  your  InformaEon  Lifecycle  Management  (ILM)  requirements  –  What  needs  to  be  archived  –  How  long  you  need  to  hold  on  to  them  

•  “We’re  an  IT  shop  delivering  business  value”  •  Today’s  IT  strategies  should  provide  an  immediate  payback  

AND  set  the  stage  for  future  innovaEon  –  Understand  your  data  –  Manage  data  growth  via  archiving  –  Use  subsets  for  test  data  creaEon  –  Mask  data  in  non-­‐producEon  environments  –  ReEre/consolidate  legacy/unused  applicaEons  

What’s the Take-Away?

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In Closing…..

Thank  You  

Disclaimers  IBM  customers  are  responsible  for  ensuring  their  own  compliance  with  legal  requirements.  It  is  the  customer's  sole  responsibility  to  obtain  advice  of  competent  legal  counsel  as  to  the  iden>fica>on  and  interpreta>on  of  any  relevant  laws  and  regulatory  requirements  that  may  affect  the  customer's  business  and  any  ac>ons  the  customer  may  need  to  take  to  comply  with  such  laws.      IBM  does  not  provide  legal  advice  or  represent  or  warrant  that  its  services  or  products  will  ensure  that  the  customer  is  in  compliance  with  any  law.  The  informa>on  contained  in  this  documenta>on  is  provided  for  informa>onal  purposes  only.  While  efforts  were  made  to  verify  the  completeness  and  accuracy  of  the  informa>on  provided,  it  is  provided  “as  is”  without  warranty  of  any  kind,  express  or  implied.  IBM  shall  not  be  responsible  for  any  damages  arising  out  of  the  use  of,  or  otherwise  related  to,  this  documenta>on  or  any  other  documenta>on.  Nothing  contained  in  this  documenta>on  is  intended  to,  nor  shall  have  the  effect  of,  crea>ng  any  warran>es  or  representa>ons  from  IBM  (or  its  suppliers  or  licensors),  or  altering  the  terms  and  condi>ons  of  the  applicable  license  agreement  governing  the  use  of  IBM  so`ware.  

Trademarks  and  disclaimers  Intel,  Intel  logo,  Intel  Inside,  Intel  Inside  logo,  Intel  Centrino,  Intel  Centrino  logo,  Celeron,  Intel  Xeon,  Intel  SpeedStep,  Itanium,  and  Pen>um  are  trademarks  or  registered    trademarks  of  Intel  Corpora>on  or  its  subsidiaries  in  the  United  States  and  other  countries./    Linux  is  a  registered  trademark  of  Linus  Torvalds  in  the  United  States,  other  countries,  or  both.  

Microso`,  Windows,  Windows  NT,  and  the  Windows  logo  are  trademarks  of  Microso`  Corpora>on  in  the  United  States,  other  countries,  or  both.    IT  Infrastructure  Library  is  a  registered  trademark  of  the  Central  Computer  and  Telecommunica>ons  Agency  which  is  now  part  of  the  Office  of  Government  Commerce.    ITIL  is  a  registered  trademark,  and  a  registered  community  trademark  of  the  Office  of  Government  Commerce,  and  is  registered  in  the  U.S.  Patent  and  Trademark  Office.    UNIX  is  a  registered  trademark  of  The  Open  Group  in  the  United  States  and  other  countries.    Java  and  all  Java-­‐based  trademarks  are  trademarks  of  Sun  Microsystems,  Inc.  in  the  United  States,  other  countries,  or  both.    Other  company,  product,  or  service  names  may  be  trademarks  or  service  marks  of  others.        Informa>on  is  provided  "AS  IS"  without  warranty  of  any  kind.  

The  customer  examples  described  are  presented  as  illustra>ons  of  how  those  customers  have  used  IBM  products  and  the  results  they  may  have  achieved.    Actual  environmental  costs  and  performance  characteris>cs  may  vary  by  customer.  

Informa>on  concerning  non-­‐IBM  products  was  obtained  from  a  supplier  of  these  products,  published  announcement  material,  or  other  publicly  available  sources  and  does  not  cons>tute  an  endorsement  of  such  products  by  IBM.    Sources  for  non-­‐IBM  list  prices  and  performance  numbers  are  taken  from  publicly  available  informa>on,  including  vendor  announcements  and  vendor  worldwide  homepages.    IBM  has  not  tested  these  products  and  cannot  confirm  the  accuracy  of  performance,  capability,  or  any  other  claims  related  to  non-­‐IBM  products.    Ques>ons  on  the  capability  of  non-­‐IBM  products  should  be  addressed  to  the  supplier  of  those  products.  

All  statements  regarding  IBM  future  direc>on  and  intent  are  subject  to  change  or  withdrawal  without  no>ce,  and  represent  goals  and  objec>ves  only.      

Some  informa>on  addresses  an>cipated  future  capabili>es.    Such  informa>on  is  not  intended  as  a  defini>ve  statement  of  a  commitment  to  specific  levels  of  performance,  func>on  or  delivery  schedules  with  respect  to  any  future  products.    Such  commitments  are  only  made  in  IBM  product  announcements.    The  informa>on  is  presented  here  to  communicate  IBM's  current  investment  and  development  ac>vi>es  as  a  good  faith  effort  to  help  with  our  customers'  future  planning.    

Performance  is  based  on  measurements  and  projec>ons  using  standard  IBM  benchmarks  in  a  controlled  environment.    The  actual  throughput  or  performance  that  any  user  will  experience  will  vary  depending  upon  considera>ons  such  as  the  amount  of  mul>programming  in  the  user's  job  stream,  the  I/O  configura>on,  the  storage  configura>on,  and  the  workload  processed.    Therefore,  no  assurance  can  be  given  that  an  individual  user  will  achieve  throughput  or  performance  improvements  equivalent  to  the  ra>os  stated  here.  

Prices  are  suggested  U.S.  list  prices  and  are  subject  to  change  without  no>ce.    Star>ng  price  may  not  include  a  hard  drive,  opera>ng  system  or  other  features.    Contact  your  IBM  representa>ve  or  Business  Partner  for  the  most  current  pricing  in  your  geography.  

Photographs  shown  may  be  engineering  prototypes.    Changes  may  be  incorporated  in  produc>on  models.    

©  IBM  Corpora>on  1994-­‐2008.    All  rights  reserved.  

References  in  this  document  to  IBM  products  or  services  do  not  imply  that  IBM  intends  to  make  them  available  in  every  country.  

Trademarks  of  Interna>onal  Business  Machines  Corpora>on  in  the  United  States,  other  countries,  or  both  can  be  found  on  the  World  Wide  Web  at  hip://www.ibm.com/legal/copytrade.shtml.