CSV Automated ETL

ETL the Modern Way. Get your data out of CSV so you can analyze it.

Data from a CSV file and other character delimited files (tab, space, semicolon, etc.) are read and imported into Panoply through the File Upload data source. The records in your file are ported as is into a fixed or dynamic destination table, and then the file's header rows become the table's columns.

Modernizing CSV ETL

What is ETL?

Integrating data for analytics can be especially hard in a fast-shifting, rapid growth startup environment, where relevant business data might be spread out across a collection of apps and spreadsheets. ETL (Extract, Transform, Load) tools will help you collect your data from APIs and file transfers (the Extract step), convert them into standardized analytics-ready tables (the Transform step) and put them all into a single data repository (the Load step) to centralize your analytics efforts.

The shift to ELT

The traditional ETL model is a relic of the pre-cloud era, when compute resources were expensive, and everything needed to be cleaned up before analysis. These days, moving the transformation step closer to the time of analysis is not only feasible, it’s desirable. ELT lets you load raw data, increasing your analytical flexibility and moving relevant data more quickly from your engineering team to your analytics and BI teams.

All in one CSV data pipeline

Panoply’s 80+ data connectors and built-in automated cloud data warehouse will let you go from a collection of siloed datasets to sophisticated analyses that integrate your CSV data in a matter of minutes. Panoply is the only tool that combines an ETL process with a data warehouse, giving you total control over your data from sync to storage. We’ll handle all the infrastructure so you can skip the engineering work and go straight to analysis with your favorite BI tool.

CSV