SnapLogic ELT Use Cases

ETL (Extract, Transform, and Load). It supports today’s data-driven businesses and defines a three-step process.

  • Extraction: Raw data is obtained from varied sources (such as a database or an application).

  • Transformation: The data is modified, cleaned, and normalized so that it becomes easier for the end-user to read. 

  • Loading: Once the data is transformed, it is loaded into a target endpoint, a database.

Explore the following ELT use cases that demonstrate how the SnapLogic ELT Snap Packscan help solve complex data migration problems that users face in their day-to-day data-driven businesses

Using ELT Snap Pack to Achieve Faster-time to Value Data: Go through this use case to discover ELT Snap Pack helps users build an incremental query to extract, load, and transform data for retrieving a customer's order data from the database. With the help of ELT Snaps, customers can manage multiple orders, and huge volumes of data while meeting tight deadlines and utilizing optimum resources. To drive business growth using analytics and data insights, enterprise applications must be able to get customers' order data quickly and easily.

Analyze Customer Returns For Retail Stores Chain: Explore this use case to understand how the orders and returns are are handled in the retail industry using ELT Snap Pack. This example demonstrates the process to find customers who have returned items worth 20% more often than the average customer returns for a store in a given state for a given year.