Data matching means different things to different people.

To people in the financial world it’s often joining or matching, ‘mismatching’ data, describing general financial records like payroll, purchases, expenses, revenue, payments, and P&L.

To people in supply chain operations it might be matching ‘mismatching’ data describing supplier details, items purchased, purchase orders, invoices, and payment details.

To people in sales and marketing it’s often matching ‘mismatching’ sales and marketing data, trying to reconcile contact details for different people and companies.

Data Analysts, Data Engineers, and people in Business Intelligence are also often ‘cleaning’, ‘standardizing’ and reconciling ‘mismatching’ data from multiple sources.

In technology, each time we integrate systems or deploy new technology we’re usually linking or integrating ‘mismatching’ data from different sources.

To people in master data management it’s a challenge of consolidating ‘mismatching’ data from all critical areas of business, describing contacts, accounts, locations, products and services, into a single source of truth.

This concept of consolidating ‘mismatching’ data from different sources, is something that exists in almost all areas of business. But most people still do it in Excel, eyeballing row after row.

Match Data Pro is an easier way to clean, match, and manage data.

Author: Ben Cutler

Inquiries: bcutler@matchdatapro.com