SlideShare une entreprise Scribd logo
1  sur  15
Migration Madness
The Science of Data Migration
Stephen Porter, CEO, Zero Wait-State
Title Slide
FACTS ABOUT ZWS - Facts About
Important IN OUR DNA

Zero Wait-State

Data Migration is in our DNA
 Our Name
 Our History

Zero Wait-State - Company Confidential
FACTS ABOUT ZWS - NEUTRAL
Important Facts About

Zero Wait-State

We are Vendor and Partner Neutral
 Associate Service Partner and Research Associate for SolidWorks
 Oracle Gold Partner
 PLM and PDM Services only

Zero Wait-State - Company Confidential
DM IS HARD

Zero Wait-State - Company Confidential
DM IS CRITICAL

Zero Wait-State - Company Confidential
BEST PRACTICES INCREMENTS

Zero Wait-State - Company Confidential
BEST PRACTICIES FORGET IT

Zero Wait-State - Company Confidential
Garbage In, Garbage Out …

Zero Wait-State - Company Confidential
Be Prepared

Zero Wait-State - Company Confidential
Test, Validate, Repeat

Zero Wait-State - Company Confidential
Case Study : Bloom Energy

Zero Wait-State - Company Confidential
Data migration Presentation

Contenu connexe

Similaire à Data migration Presentation

Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...
Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...
Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...
Hugo van Hoogstraten
 
SVI Pitchbook
SVI PitchbookSVI Pitchbook
SVI Pitchbook
SVI2014
 

Similaire à Data migration Presentation (20)

2013 Dec 9 Data Marketing 2013 - Hadoop
2013 Dec 9 Data Marketing 2013 - Hadoop2013 Dec 9 Data Marketing 2013 - Hadoop
2013 Dec 9 Data Marketing 2013 - Hadoop
 
2014 feb 24_big_datacongress_hadoopsession2_moderndataarchitecture
2014 feb 24_big_datacongress_hadoopsession2_moderndataarchitecture2014 feb 24_big_datacongress_hadoopsession2_moderndataarchitecture
2014 feb 24_big_datacongress_hadoopsession2_moderndataarchitecture
 
ZIGRAM Introduction July 2021
ZIGRAM Introduction July 2021ZIGRAM Introduction July 2021
ZIGRAM Introduction July 2021
 
Cleared Job Fair Job Seeker Handbook May 7, 2015, Crystal City, Va
Cleared Job Fair Job Seeker Handbook May 7, 2015, Crystal City, VaCleared Job Fair Job Seeker Handbook May 7, 2015, Crystal City, Va
Cleared Job Fair Job Seeker Handbook May 7, 2015, Crystal City, Va
 
Why you using bpo outsourcing
Why you using bpo outsourcingWhy you using bpo outsourcing
Why you using bpo outsourcing
 
Cleared Job Fair Job Seeker Handbook Sept 4, 2014, Springfield, VA
Cleared Job Fair Job Seeker Handbook Sept 4, 2014, Springfield, VACleared Job Fair Job Seeker Handbook Sept 4, 2014, Springfield, VA
Cleared Job Fair Job Seeker Handbook Sept 4, 2014, Springfield, VA
 
Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...
Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...
Data Quality Challenges to Big Data_Practical Insights_KPMG Presentation 20.4...
 
Webinar - Risky Business: How to Balance Innovation & Risk in Big Data
Webinar - Risky Business: How to Balance Innovation & Risk in Big DataWebinar - Risky Business: How to Balance Innovation & Risk in Big Data
Webinar - Risky Business: How to Balance Innovation & Risk in Big Data
 
Cleared Job Fair Job Seeker Handbook Nov 20, 2014, Crystal City, VA
Cleared Job Fair Job Seeker Handbook Nov 20, 2014, Crystal City, VACleared Job Fair Job Seeker Handbook Nov 20, 2014, Crystal City, VA
Cleared Job Fair Job Seeker Handbook Nov 20, 2014, Crystal City, VA
 
Daniel Murphey - Startup lessons for marketers
Daniel Murphey - Startup lessons for marketersDaniel Murphey - Startup lessons for marketers
Daniel Murphey - Startup lessons for marketers
 
SVI Pitchbook
SVI PitchbookSVI Pitchbook
SVI Pitchbook
 
Next Generation Hadoop Introduction
Next Generation Hadoop IntroductionNext Generation Hadoop Introduction
Next Generation Hadoop Introduction
 
Cloudera 助力台灣大數據產業的發展
Cloudera 助力台灣大數據產業的發展Cloudera 助力台灣大數據產業的發展
Cloudera 助力台灣大數據產業的發展
 
'Agile Software Delivery: No Longer A Nice To Have': Robert Benefield @ Colom...
'Agile Software Delivery: No Longer A Nice To Have': Robert Benefield @ Colom...'Agile Software Delivery: No Longer A Nice To Have': Robert Benefield @ Colom...
'Agile Software Delivery: No Longer A Nice To Have': Robert Benefield @ Colom...
 
The Many Faces of SHIELD
The Many Faces of SHIELDThe Many Faces of SHIELD
The Many Faces of SHIELD
 
Tracking firm presentation (vincent wedelich) mmm
Tracking firm presentation (vincent wedelich) mmmTracking firm presentation (vincent wedelich) mmm
Tracking firm presentation (vincent wedelich) mmm
 
Tracking firm presentation (vincent wedelich) mmm 3M
Tracking firm presentation (vincent wedelich) mmm 3MTracking firm presentation (vincent wedelich) mmm 3M
Tracking firm presentation (vincent wedelich) mmm 3M
 
Jason Tooley – Welcome to Vision Solution Day EMEA
Jason Tooley – Welcome to Vision Solution Day EMEAJason Tooley – Welcome to Vision Solution Day EMEA
Jason Tooley – Welcome to Vision Solution Day EMEA
 
Using Data To Tranform Your Business - Marketing Business
Using Data To Tranform Your Business - Marketing BusinessUsing Data To Tranform Your Business - Marketing Business
Using Data To Tranform Your Business - Marketing Business
 
Dr Harvey Lewis - Trends in Big Data, Key Challenges for Skills
Dr Harvey Lewis - Trends in Big Data, Key Challenges for SkillsDr Harvey Lewis - Trends in Big Data, Key Challenges for Skills
Dr Harvey Lewis - Trends in Big Data, Key Challenges for Skills
 

Plus de Zero Wait-State

Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)
Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)
Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)
Zero Wait-State
 
Moving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial ManufacturingMoving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial Manufacturing
Zero Wait-State
 
Learn More About PDXState Stand Alone Viewer
Learn More About PDXState Stand Alone ViewerLearn More About PDXState Stand Alone Viewer
Learn More About PDXState Stand Alone Viewer
Zero Wait-State
 
ECAD 231 Functional Overview
ECAD 231 Functional OverviewECAD 231 Functional Overview
ECAD 231 Functional Overview
Zero Wait-State
 
Epdm Agile Webinar 3 2010 F
Epdm Agile Webinar 3 2010 FEpdm Agile Webinar 3 2010 F
Epdm Agile Webinar 3 2010 F
Zero Wait-State
 

Plus de Zero Wait-State (18)

Oracle value chain summit 14
Oracle value chain summit 14Oracle value chain summit 14
Oracle value chain summit 14
 
Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)
Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)
Zws e bom2mbom discovery and recommendation process_agileec_v1 0 (2)
 
Moving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial ManufacturingMoving Up the PVC Maturity Curve in Industrial Manufacturing
Moving Up the PVC Maturity Curve in Industrial Manufacturing
 
PLM Implementation
PLM ImplementationPLM Implementation
PLM Implementation
 
Learn More About PDXState Stand Alone Viewer
Learn More About PDXState Stand Alone ViewerLearn More About PDXState Stand Alone Viewer
Learn More About PDXState Stand Alone Viewer
 
Integration Solutions
Integration Solutions  Integration Solutions
Integration Solutions
 
Migration madness
Migration madnessMigration madness
Migration madness
 
The power of pdx state
The power of pdx stateThe power of pdx state
The power of pdx state
 
ECAD 231 Functional Overview
ECAD 231 Functional OverviewECAD 231 Functional Overview
ECAD 231 Functional Overview
 
Zws webinar september 2012 operational excellence series v14
Zws webinar september 2012 operational excellence series v14Zws webinar september 2012 operational excellence series v14
Zws webinar september 2012 operational excellence series v14
 
Design State - EPDM to AGILE
Design State - EPDM to AGILEDesign State - EPDM to AGILE
Design State - EPDM to AGILE
 
DesignState Intralink to AgilePLM
DesignState Intralink to AgilePLMDesignState Intralink to AgilePLM
DesignState Intralink to AgilePLM
 
New Engineering Client for Agile PLM
New Engineering Client for Agile PLMNew Engineering Client for Agile PLM
New Engineering Client for Agile PLM
 
Medical Device Agile Quality Demo
Medical Device Agile Quality DemoMedical Device Agile Quality Demo
Medical Device Agile Quality Demo
 
Epdm Agile Webinar 3 2010 F
Epdm Agile Webinar 3 2010 FEpdm Agile Webinar 3 2010 F
Epdm Agile Webinar 3 2010 F
 
Zero Wait-State Agile EC MCAD Implementation Quick Start Presentation
Zero Wait-State Agile EC MCAD Implementation Quick Start PresentationZero Wait-State Agile EC MCAD Implementation Quick Start Presentation
Zero Wait-State Agile EC MCAD Implementation Quick Start Presentation
 
Zws Seminar 20 Minutes
Zws Seminar 20 MinutesZws Seminar 20 Minutes
Zws Seminar 20 Minutes
 
Zws Corporate Presentation Agile Implementation Approach
Zws Corporate Presentation  Agile Implementation ApproachZws Corporate Presentation  Agile Implementation Approach
Zws Corporate Presentation Agile Implementation Approach
 

Dernier

CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
giselly40
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
Joaquim Jorge
 

Dernier (20)

From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
Slack Application Development 101 Slides
Slack Application Development 101 SlidesSlack Application Development 101 Slides
Slack Application Development 101 Slides
 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
GenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day PresentationGenCyber Cyber Security Day Presentation
GenCyber Cyber Security Day Presentation
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024Finology Group – Insurtech Innovation Award 2024
Finology Group – Insurtech Innovation Award 2024
 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
 
A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024A Call to Action for Generative AI in 2024
A Call to Action for Generative AI in 2024
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men08448380779 Call Girls In Friends Colony Women Seeking Men
08448380779 Call Girls In Friends Colony Women Seeking Men
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
The Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptxThe Codex of Business Writing Software for Real-World Solutions 2.pptx
The Codex of Business Writing Software for Real-World Solutions 2.pptx
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 

Data migration Presentation

Notes de l'éditeur

  1. There is a famous quote from the philosopher George Santayana saying, "Those who cannot remember the past are doomed to repeat it." George obviously has never been involved in data migration projects. History from PDM and PLM systems adds a degree of complexity to a migration that can be prohibitive. Extracting and capturing history from legacy PLM and PDM systems is very challenging. Ensuring that this information gets accurately transmitted into a target system can be even more problematic depending upon the sophistication of the import utilities. Using a "latest only" approach dramatically lessens the complexity of the migration and most companies discover that their history wasn't that useful. If it is absolutely necessary to preserve the history some companies will elect to keep their legacy system around or virtualize it and let people access it on an "as-needed" basis. It turns out for most companies that the need is surprising less than they expected. This also addresses some of the issues I mentioned above related to "garbage in garbage out" and "volume, volume, volume".
  2. One of the first mistakes companies make when embarking upon a data migration project is assuming their current data structure is worthy of migration. Over the year companies accumulate a large amount of information and not all of it is critical to the company going forward and not all of it is in a condition that will make it useful in the new system. This would be a good time to take a hard look at your legacy data and determine what really needs to come over into the new system. Older product information may no longer be relevant and some information is not structured in a way to be useful in a PLM system. Obviously when you are moving from a PDM or PLM tool into a new PLM tool you are able to capture useful metadata like attributes but many companies migrate from system disks to PLM which can be much more challenging. Time needs to be spent evaluating current data and how relevant it is for future product development needs. Also if data is corrupted or sub optimal you should think hard before polluting the new system with the data.
  3. The famous Boy Scout motto applies to many things but especially to PLM data migration. Preparation starts with hardware. It is a big mistake to under provision servers for this type of effort particularly if you are planning to move a lot of data. The other thing to be prepared with is a good set of data analysis and cleaning tools. As we discussed above understanding the condition of your data and being able to automate some of the cleanup can be very impactful. In most cases particularly with metadata there are scripts and applications to detect naming conflicts and to validate data transmission on the backend. It is important that you either have these capabilities or work with someone who does. You need to walk through the analysis process and understand the condition of your data so you are not caught off guard by the level of cleanup you will need on the back end of the migration. Ideally you should do as much clean-up as possible prior to moving information into the target system. It is infinitely easier to clean up information prior to migrating into a new PLM tool.
  4. It is almost impossible to test too much during a data migration. We recommend two test passes minimum which should allow you to go into a test system and thoroughly sample the data before eventually moving to production. A well considered test plan should be included for the project either developed internally or with a partner's assistance. Ad hoc testing is better than nothing but there is a good possibility that you could miss something. Generic test plans are better than ad hoc testing but again without tailoring something specific for your environment you may find out the hard way that something is missing or wrong. If your company is required to validate per FDA or other regulations you can combine some of this effort into testing and potentially compress your testing cycle. It is best to get testing addressed up front before the project gets too far down the road. The temptation to truncate testing is great so you must resist.
  5. This is more of an issue for companies who are downsizing or as they like to say "rightsizing". Companies that elect to move from a more sophisticated PLM to a more affordable solution or an easier to use system can run into issues where they have more information to move than the new system can accommodate. Examples of this might be moving from Agile Advantage to Arena or from Intralink or PDMLink to Enterprise PDM(EPDM). The source system might support more data type or attributes than the new system can deal with so you need to take this into account when preparing the information to move over. More appropriately you need to consider this before you make the decision to move. If any of the information is critical you may be in for an unpleasant surprise. Workflows, Change history, file attachments, and access control logic are all things that may not be accommodated when moving from one vendor to another.