How to Perform Data Dictionary Mapping for Seamless Data Integration
                     How to Perform Data 
Dictionary Mapping for 
Seamless Data 
Integration
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Introduction to Data Dictionary Mapping
• Data integration across systems is continuous in today’s 
environment.
• Data dictionary mapping ensures consistency and 
accuracy across platforms.
• This process aligns data elements from collecting and 
receiving systems.
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What is Data Dictionary 
Mapping?
• It matches data fields from one system’s dictionary to 
another’s.
• A data dictionary catalogs metadata like name, type, 
and allowed values.
• E.g., mapping DOB from one system to Birth_Date in 
another ensures consistency.
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Importance and Benefits of Data Dictionary 
Mapping
• Poor mapping leads to errors, data loss, or compliance 
risks.
• Ensures accurate data integration and integrity across 
systems.
• Helps with interoperability, compliance, onboarding, 
and vendor transitions.
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Determine Scope and 
Objectives
• Clarify which systems and data domains are being 
integrated.
• Define if the goal is migration, synchronization, or 
standardization.
• Align the mapping service with clear business 
requirements.
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Gather Dictionaries & Normalize 
Metadata
• Obtain data dictionaries or build one using profiling if 
missing.
• Collect field names, types, constraints, and 
relationships.
• Normalize metadata by removing duplicates and 
standardizing terms.
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Identify Mapping 
Relationships
• Determine relationships: one-to-one, one-to-many, 
etc.
• Apply transformation logic where formats differ (e.g., 
date formats).
• Use mapping tables/spreadsheets to track 
relationships and rules.
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