Which Approach to Choose: Mapping vs. Other Alignment Methods

📌 Overview

In cofi.ai, there are several ways to align data across systems — Mapping, Database Joins, and Relationships.

Each serves a different purpose depending on your data structure and how consistently your dimensions are named.

This article helps you choose the right approach for your situation — balancing flexibility, accuracy, and ongoing maintenance needs.

Approach	Primary Use	Description
Column Mapping	Standardizing categorical values	Translates inconsistent names from different systems (e.g.,”HR”, “Human Resources” ) into one single, consistent label
Relationship mapping	Structuring data hierarchically	Connects one-to-many or parent-child datasets (e.g., Department → Sub-department) to enable drill-down analysis and aggregated roll-ups
Database Join	Combining related metrics or dimensions from different tables	Links datasets that share a common identifier (e.g., Company_ID, Account_Code)

💡 Tip: Mapping focuses on data consistency (naming), while Joins and Relationships handle data connectivity (structure).

You have naming inconsistencies between systems (e.g., “HR” vs. “Human Resources”).
You want to clean and unify data without altering original source values.

Example: Unifying “U.S.”, “United States”, and “America” under “United States.”

Example: Linking “Department → Team → Employee” for multi-level reporting.