The Data Integration Process: How to Put Your Data to Work With iPaaS

The Data Integration Process: How to Put Your Data to Work With iPaaS

Data integration is a well-established practice that has been around for decades. The traditional method, known as Extract, Transform, Load (ETL), has been in use since the 1970s. It involves gathering data from multiple sources, modifying it as needed, and storing it in a central database. While ETL has proven to be dependable, it has limitations such as being slow, inflexible, and primarily compatible with on-premises systems. This means that valuable data stored in the cloud remains isolated and inaccessible.

To overcome these limitations, the modern approach to data integration is the use of an integration platform as a service (iPaaS). iPaaS also gathers data from various sources and standardizes it for easier analysis. However, the key advantage of iPaaS over ETL is its ability to integrate with both on-premises systems and cloud-based data sources. Additionally, iPaaS goes beyond data integration by seamlessly connecting applications themselves. This enables real-time accessibility and utilization of data from any source, including employees, AI, machines on the factory floor, and other automated business resources.

Read the full article from Boomi here.