<aside> 🧭

Navigation:

</aside>

Summary

This white paper provides an overview and a detailed view of pitfalls making painful a data migration related to Dynamics 365 or Dynamics CRM. Regardless the type of data migration (migration to Dynamics online or migration to Dynamics On-Premises), native and custom items could delay the data migration process. Those items should be categorized into 5 groups: data context, platform context, functional context, code context, architecture context.

Keywords

Data Migration, D365, Dynamics 365 On-Premises, Dynamics CRM On-Premises, Orchestration, Guide, Ordering, Prioritization, Grouping, Reporting, Logging, Tables, Attributes, Columns, Entities, Data Model, Customer Data Model, Activity Data Model, Custom Entities, System Entities, Core Data Model, Security Data Model, Internal System Process, Sequencies, Validation.

Confidentiality

The white paper does not provide any confidential client data related to data migration. All the code in this white paper is only related to the CRM SDK365 code.

INTRODUCTION: MIGRATION CONTEXT

Data Migration options

Without emphasizing the technical aspect of an option, in this case, whether it is a "Cloud" technology (cloud technology) or an "on Premise" technology, there are two execution contexts:

OPTION DATA SOURCE DATA DESTINATION DESIGN OF SCENARIO
TYPE A DATABASE (DB) DATABASE (DB) DB/DB
TYPE B DATABASE (DB) SERVICE DB/SERVICE

Data migration options applied to Dynamics CRM

Emphasizing the technical aspect of an option, what does it mean regarding the platform Dynamics CRM or Dynamics 365?

OPTION DATA SOURCE DATA DESTINATION DESIGN SCENARIO DYNAMICS 365
TYPE A DATABASE DATABASE DB/DB FROM DYNAMICS ON-PREM TO DYNAMICS ON-PREM
TYPE B DATABASE SERVICE DB/SERVICE FROM DYNAMICS ON-PREM TO DYNAMICS ON-LINE

Pitfalls of a data migration

A data migration focuses on the movement of data between source (legacy data system and business) and destination (target system).  However, pitfalls related to the CRM data context are real and can delay the data migration: data related to security model, data related to shared data, data model related to denormalization, data logs and audit and finally, data volume.

Even with the most thoroughly tested tools and procedures, we need to ask ourselves how to orchestrate a data migration, mainly from database to database.