Glossary
Data Integration

Data Integration

Published

April 22, 2026

Last updated

April 22, 2026

Definition

Data integration is the process of combining data from different sources into a single, unified, and consistent view. This process involves discovering, cleaning, monitoring, and transforming data to make it more useful for analysis and business decision-making.

In the context of business planning, data integration is fundamental to creating a single source of truth. It allows organizations to connect financial data from an ERP system with operational metrics from sales, marketing, and HR platforms, enabling a holistic view of performance and more accurate forecasting.

Effective data integration breaks down data silos, supporting comprehensive integrated business planning (IBP) by ensuring that strategic, financial, and operational plans are based on the same underlying information. This consistency is critical for reliable reporting, variance analysis, and building trust in planning models across the organization.

Frequently Asked Questions

What are data integration tools?

Data integration tools are software applications and platforms that automate the process of collecting, combining, transforming, and managing data from disparate sources.

What is the difference between data integration and ETL?

Data integration is the broad strategy and process of combining data from various sources, while ETL (Extract, Transform, Load) is a specific, common architectural pattern used to execute that strategy.

What are the types of data integration?

Common types of data integration include data warehousing (often using ETL/ELT), data virtualization (providing a unified view without moving data), and application-based integration which uses APIs to synchronize data between applications.

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