Good data.
By definition.
DataRaft turns incoming data into checked, reusable data for your reports. Set the rules once, run them on every delivery, and know which version produced the result.
See how DataRaft worksFrom raw data to an answer you can explain.
- 01 / CONNECT
Bring data in
Files, databases and APIs.
- 02 / PREPARE
Shape it
Reusable R steps and models.
- 03 / CHECK
Apply the rules
Expected columns, keys and quality.
- 04 / KEEP
Save a version
Accepted data and check evidence.
- 05 / USE
Explain the result
Reports, metrics and lineage.
Start with the story. Then try it in R.
Learn the idea in plain English or build your first checked product.
See the idea in plain English
Follow one monthly report from incoming data to an explainable result.
Explore ↗READY TO USE RMake your first checked product
Five short chapters, beginning with an in-memory example.
Explore ↗LEARN BY DOINGFollow the full R course
Work through a downloadable script with guided exercises.
Explore ↗Data Platforms with R.
From scripts to governed data products with DataRaft. A complete technical book with architecture, runnable workflows, exercises and an end-to-end insurance case.
Read the book →DataRaft step by step.
From local data and quality checks to DuckLake and Positron. Small exercises, one continuous example and a complete R script.
Explore the course →Try DataRaft in R.
The metapackage gives you the common commands. Its specialist packages add storage, connections, metrics and editor support.
install.packages("pak")
pak::pak("dataraft-r/dataraft")DataRaft is development software. Its APIs and integrations are experimental. Read the compatibility guide before using it in a production environment.