The term ETL (Extract, Transform, Load) indicates the process of data preparation, coming from various sources and their subsequent organization and centralization in a single repository. Through the ETL process, the data acquire a high level of quality, so that they can be used for various operations:
- Data Migration from one application to another;
- Data replication for backup or redundancy analysis;
- Data entry into a Data Warehouse for assimilation, sorting, and transformation into business intelligence;
- Synchronization of key systems.
ETL stands for the three key Data Preparation processes, namely:
Extract – Raw data is extracted from various sources, such as databases, activity logs, reports on anomalies, security events and other transactional activities;
Transform – in this phase, the data undergoes a transformation through the application of a series of rules defined at the company level (standardization, deduplication, verification). Through the transformation, what was initially raw and unusable, is shaped into a set of data ready for the last phase of the ETL process, that of loading.
Load – the last act of the entire ETL process involves loading the extracted and transformed data into a new destination (for example Data Mart, Data Warehouse).
The ETL process is functional to prepare data that will be used to display beautiful Dashboards with Tableau Software.