The process of taking data from different systems and putting it into a data warehouse for business analysis can be a complicated affair. In this article, we look at what is involved and how the cloud has made matters potentially trickier.

A data warehouse is a relational database that is designed for query and analysis rather than for transaction processing. It usually contains historical data derived from transaction data, but it can include data from other sources..

Modern enterprises gather data from many disparate sources, including social media, websites, customer databases (CRM systems, sales records etc), customer support systems, and HR software.

Merely collecting lots of data isn't useful in itself—it's the insights you get from such data that can drive more informed business decisions. This post aims to teach you about the bedrock processes required for obtaining insights from your data—ETL and ELT.

We'll begin by discussing data integration, before moving on to two vital forms of data integration—ETL and ELT. When you're finished reading, you'll fully understand what ETL and ELT are, and which process is better suited to your business in terms of getting actionable insights from different data sources..