Data warehouses, databases, data lakes, or data hubs have become key growth drivers for technology-driven businesses of all sizes. There are several factors that contribute to the successful building and management of each of these data systems. The ETL (Extract, Transform, Load) strategy is the most important of them all. Nowadays, there are several best ETL tools in the market which allow businesses to design robust data systems. They are differentiated into open source and enterprise ETL tools on the basis of their implementation. This post is not focused on the best ETL tools in the market, nor does it compare ETL tools. What should you expect then? This post intends to build your understanding of the ETL processing and parameters to be checked before investing in an ETL tool.
Understanding the Basics of the ETL Processing
When developing a database, it becomes important to prepare and store data in comprehensible formats. ETL comprises three distinct functions (Extract, Transform, and Load) that are integrated in a single tool, which aids in the data preparation and storage required for database management.