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1 © Copyright 2016 Dell. All rights reserved.
How To Migrate Existing Documentum Application to the D2-Based Life Sciences Suite Kirstin Dreyfürst
fme Representative
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Kirstin Dreyfürst Life Science Competency Center Leader Principal Consultant [email protected] Kirstin Dreyfuerst @kirdreyde
How to Migrate to D2 or LSSSuite
Introduction
Use cases
Migration steps
Challenges
Validation approach
Migration scenarios and examples
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fme Who we are
Facts • Partner for digital transformation in
life sciences, industrial manufacturing and more
• ECM, BI, Cloud, Big Data, Social Collaboration & Custom Software Development
• Consulting, Concept, Development, Maintenance, Products
• Founded in 1995 • 175 employees,
20 Mio. € total revenue • Offices in Germany, Romania, USA • It‘s fme you love to work with!
INTRODUCTION
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Overview Migration
• Old system(s) • Old process • Old data
?
• New system • New process • «Old» adapted
data #320169© fme AG 6
Overview Migration
• Old system(s) • Old process • Old data
?
• New system • New process • «Old» adapted
data
Transforming data Enhancing data Adapting data Match controlled value
lists
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Little Controlled System with Custom Types
Unstructured Systems
FirstDoc Dictionaries Object Types Rules
Overview Migration to D2 / LSSSuite
Other ControlledSystem
Dictionaries, Taxonomies
Object Types of LSSSuite
D2 / LSSSuite Rules
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Migration Options
- For higher volume - Quicker than migration - Keep IDs - Keep uncleaned data - Downtime needed
- Easy for low volume - Possible with short downtime
- Takes time for high volume
- Time and resources for manual work needed - Risk of loss due to manual failures
- Easy for low volume with inconsistent data
• In-place conversion
• Data migration
• Manual (start empty)
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USE CASES
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Use Case: One System – High Volume
• Transforming data needs time
In-Place Approach • Change application
directly in-place • In-place transfer of data
(all at once) • Legacy data stays
unusable in system • Long downtime needed • Audit trail and IDs remain
Migration Approach • Clean data • Start with batches • Complete batches • Migrate delta • Audit trail can be
migrated
Manual • Not feasible
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Use Case: One System – Low Volume
• Transforming data is quick
In-Place Approach • Change application
directly in-place • In-place transfer of data • Keep unclean and legacy
data • Short downtime needed • Audit trail and IDs remain
Migration Approach • Clean data • Big Bang approach or
batch approach • Audit trail can be
migrated
Manual • Possible • Time and resources
needed
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Use Case: Consolidation into One System
• Transforming data is quick
In-Place Approach • Not possible
Migration Approach • Batches from different
systems • Complete batches • Migrate delta • Dictionary consolidation
Manual • Possible for low
volume batches • Lots of time and
resources needed • Manual creation of
dictionaries
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Migration Steps
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Migration Steps
• Data analysis Structures and consistency
• Data cleaning Integrate new areas, archive old ones, correct errors
• Handle legacy structures
• Enhance data − add information
• Adapt data / transform to dictionary values
• Define rules for all attributes and information
• Data mapping #320169© fme AG 15
• Create manageable batches • Define parallel processes
• Data analysis Structures and consistency
• Data cleaning Integrate new areas, archive old ones, correct errors
• Handle legacy structures • Create manageable batches • Define parallel processes
Migration Steps
• Verify rules • Tests on old data • Tests on current data • Tests on different areas • Run testcycles
• Enhance data • add information
• Adapt data / transform to dictionary values
• Define rules for all attributes and information
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• Correct rules • Finalize rules
Migration Steps
• Import documents
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Migration Steps
Transformation always needed, independent of migration approach!
Input and definitions from business representatives needed!
Understanding needed: Process old new! Manual
In Place
Migration
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CHALLENGES
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Challenge – Legacy Data
• Data changes for „good“ and „bad“ data • Solutions for legacy data • New processes with old data
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Challenge – High Volume • A: Migrate in Batches
− Run old and new system in parallel − Migrate batch, start working in new system − Work on old system until migration is completed
• B: Big Bang: Pre-migrate and take Deltas − Working on old system − Migrate in parallel into new system − Readonly access during last deltas − Golive with Big Bang - all at once
• C: Inplace − Plan for a longer downtime − Golive with Big Bang - all at once
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Challenges – Business Resources
• Business Input and Decisions − Input for rules, specification − Processes
− Input about old and new − Mapping old new
− Value Lists / Dictionaries − Mapping old data value lists − Handling legacy data value lists
− Legacy and Non-fitting structures − Handling of inconsistencies − Handling of error structures
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Challenges – Business Resources
• Business Input and Decisions − Input for rules, specification − Processes
− Input about old and new − Mapping old new
− Value Lists / Dictionaries − Mapping old data value lists − Handling legacy data value lists
− Legacy and Non-fitting structures − Handling of inconsistencies − Handling of error structures
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Note:
«Everybody thinks their data is perfect
until structures are found you had never thought of…»
Kirstin Dreyfürst
VALIDATION
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Validation Approach: Black Box Testing
Black Box
Validate the process as a total: Source Target
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Validation Approach: Black Box Testing
Test QA Prod
Migration setup Informal testing Official testing
Verification of production import
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MIGRATION D2 / LSSSuite - EXAMPLES-
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Standard Migration Scenario
Consolidated Target Sources Test / Staging / Production
Scan
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Migration Scenarios
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Dell EMC Webtop Dell EMC D2
• Unstructured data structured data / rule-controlled data • Data needs to be usable for D2 logic • Think about
– Autonaming – Autolinking – Workflows – Dictionaries – Taxonomies
• Easily manageable with in-place • D2 can be set up to work with old data • Only few transformation needed • Transformation needed for inconsistency in data
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CSC FirstDoc Dell EMC LSQM / LSRD
• Data adaption match LSSS rules • FirstDoc rules LSSS rules • Product and data dictionaries LSSS taxonomies • Data Change: Type / Subtype / Unit Group / Subgroup /
Artifact (Note: No 1:1 match!)
• Data enhancement: Fill up missing values
• Option A: Migration (setting up rules i.e. FDQM LSQM) • Option B: In-place: Data transformation
(some rules, takes less time, but all at once needed)
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fme migration-center
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fme migration-center
• 350+ migration projects
• 120+ migration paths for multiple platforms
• Fit for regulated systems (80% of TOP 10 / 57% of TOP 30 pharmaceutical companies use migration-center)
• High performance to manage large data volumes
»The Delta Migration Concept was the optimal approach for us, and the migration-center definitely the right tool. With this we managed to migrate all documents accurately, in auditable fashion and under observance of all regulatory
requirements.« (Paul Yuhasz, Boehringer, Project leader) #320169© fme AG 33
Summary
Don‘t be afraid of a migration! • Migration is more than data • Use the benefits
− Improve your quality, reduce sizes − get rid of non-needed data, archive data − setup better processes compatible with your data
• Migration is the chance to improvement • D2 and LSSS are strict, but on the long term improve quality • You are the expert and know your data best • We help you to manage it in the right way in the right system
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It‘s fme you love to work with.
fme AG | Wolfenbüttler Straße 33 | D-38102 Braunschweig | www.fme.de
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