What are Data Loaders?
An introduction to the Data Loaders extension, which builds data loaders step by step that turn files and API data into events and run them on a schedule
How Data Loaders work
What a data loader is made of, the workflow of standard ETL actions it runs, and what deploying it creates
Building a data loader
A walk-through building Northgate Energy's broker settlements loader step by step, from extracting a sample to running it
Mapping columns to fields
How the Map step turns columns into event fields, with data types, date formats, decimal commas, empty values, value maps, conditions and previews
Sources
The settings of each kind of data loader source (CSV, JSON, XML, Excel and custom ODSL), and dates in URLs
Deploying, running and scheduling
Deploying a data loader as a workflow and a process, running it now or for an earlier date, its schedule, its runs and run reports, alerts, and changing or deleting it
Curves and series
Making event timeseries, event curves and event options once from a data loader's events, kept on the same master data record
Fusion AI
Ask Fusion AI to propose a data loader's event type, mapping, conditions, event id and dataset id from the sample
The ETL actions
The standard private actions every data loader's workflow runs (etl_extract, etl_transform, etl_load and etl_report), their inputs, outputs and exits, and using them in your own workflows
Reference
Where data loaders and everything they deploy are kept, the settings a process passes to its workflow, the run report fields, the extension's contents, and troubleshooting