ETL (Extract, Transform, Load) is a process of extracting data from different data sources; manipulating them according to business calculations; loading the modified data into a different data warehouse. Because of the in-depth analytics data it provides, ETL function lies at the core of Business Intelligence systems. With ETL, enterprises can obtain historical, current, and predictive views of real business data. Let’s look at some ETL features that are necessary for business intelligence.
The Importance of ETL in Business Intelligence
Businesses rely on the ETL process for a consolidated data view that can drive better business decisions. The following ETL features justify the point.
High-level Data Mapping
Leveraging data and transforming them into actionable insights is a challenge with dispersed and voluminous data. Data mapping simplifies database functionalities like integration, migration, warehousing, and transformation.
ETL allows mapping data for specific applications. Data mapping helps in establishing a correlation between different data models.
Data Quality & Big Data Analytics
Huge volumes of data aren’t of much use in their r