Glossary
Commonly Used Abbreviations and Definitions in Data Migration
A practical glossary of common migration terminology, abbreviations and definitions used throughout data migration projects.
Overview
Key migration terminology explained
Data migration projects often involve technical terminology, delivery acronyms and process language that can become difficult to track across teams and stakeholders.
This glossary provides clear explanations for the most commonly used abbreviations and definitions encountered during migration planning, extraction, validation, transformation and deployment activities.
Need clarification?
Understanding the terminology used in migration projects helps improve communication between technical teams, SMEs and stakeholders.
Topics covered
- Migration abbreviations
- Technical terminology
- Data quality concepts
- Migration delivery terms
- Testing and validation language
Reference
Abbreviations
- API — Application Programming Interface
- BIDM — Business Integrated Data Migration
- CRM — Customer Relationship Management
- CSV — Comma Separated Values
- DBA — Database Administrator
- DM — Data Migration
- DP — Delivery Phases
- DQ — Data Quality
- DV — Data Verification
- ECM — Electronic Content Management
- EDW — Enterprise Data Warehouse
- ERP — Enterprise Resource Planning
- ETL — Extract, Transform, Load
- ICT — Information, Communication, Technology
- JSON — JavaScript Object Notation
- LA — Landscape Analysis
- MDM — Master Data Management
- REST — Representational State Transfer
- SOAP — Simple Object Access Protocol
- SFTP — Secure File Transfer Protocol
- SH — Stakeholder
- SIT — System Integration Testing
- SME — Subject Matter Expert
- SS — Spreadsheets
- SSIS — SQL Server Integration Services
- UAT — User Acceptance Testing
- XML — eXtensible Markup Language
Reference
Definitions
- Business Integrated Data Migration (BIDM) — Our proprietary methodology used to keep migration projects structured and on track.
- Data Migration — The process of transferring data from one system to another during upgrades, replacements or consolidations.
- Legacy System — An older system being replaced or upgraded by a newer platform.
- Data Objects — Logical subsets of business information such as customers, suppliers or employees.
- Target System — The destination system where migrated data will reside.
- Data Mapping — The process of defining relationships and transformations between source and target data.
- Data Transformation — The conversion of source data into the format required by the target system.
- Data Cleansing — The process of correcting and standardising data before migration.
- Data Extraction — Retrieving data from source systems for migration processing.
- Data Loading — Inserting transformed data into the target system.
- Data Validation — Verifying migrated data is accurate, complete and consistent.
- Data Owner — The individual or group responsible for data approval and signoff during migration.
- Data Quality — A measure of data accuracy, consistency and completeness.
- DM Package — A collection of migration documentation, mapping specifications and validation approaches.
- Data Integration — Combining data from multiple systems into a unified structure.
- Data Conversion — Changing data from one structure or format into another.
- ETL (Extract, Transform, Load) — A migration process involving extraction, transformation and loading stages.
- Data Profiling — Analysing data structure, content and quality before migration.
- Data Governance — The policies and processes used to manage organisational data assets.
- Data Reconciliation — Comparing source and target data after migration to verify consistency.
- Legacy Data — Data held within legacy systems that is scheduled for migration.
- Data De-duplication — Removing duplicate records to improve quality and consistency.
- Data Staging — A temporary area used for preparing and transforming migration data.
- Landscape Analysis — The discovery and cataloguing of legacy data sources and relationships.
- Data Archiving — Securely storing historical data for retention and compliance purposes.
- Data Migration Strategy — A detailed plan outlining migration goals, methods and resources.
- Incremental Data Migration — Migrating data in smaller batches over time rather than all at once.
- Data Cutover — The transition point where the target system becomes operational.
- Data Migration Testing — Validation activities ensuring migrated data is production ready.
- Data Model — A conceptual representation of data structures and relationships.
- Metadata — Descriptive information about data structure, usage and relationships.
- Data Migration Tools — Applications and utilities designed to automate migration activities.
- Data Masking — Protecting sensitive information by replacing it with obscured values.
- OBJECTS — See Data Objects.
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