Singer is an open source tool that helps bring order to the messy world of custom ETL scripts. Singer allows users to mix and match inputs and outputs, making their ETL processes much more modular–and therefore easier to run and maintain. Singer uses JSON to move all data between sources and destinations, so you won’t have to worry about incompatible formats once you’ve set your ETL tasks up to run. Panoply’s integration with Singer makes it easy to move data from anywhere with a supported tap–Singer’s term for a data collection script–into an automated cloud warehouse. And since Singer is open source and supported by a broad community of developers, if you can’t find the tap you need, you can just write your own, without having to worry about building loading functions for Panoply.
Let’s face it: R may be your preferred way to do to perform machine learning and analytics. It has everything: dplyr, gglot, and shiny—maybe your own packages. But your business users just can’t hang. Supporting both is no problem with Panoply. We make it easy to sync data from 30+ data sources to multiple analytics tools, no code required.
Along with eliminating tedious setup and maintenance, Panoply’s built-in storage makes your queries faster, your pipelines more robust, and ensures that all your reporting is based on a single source of truth. Don’t choose between R and the BI tool your coworkers rely on—power both with Panoply.