Analytics & BI
Query it at scale, then put it in front of people.
Querying and visualizing what you built
Trino is the distributed SQL engine behind interactive analytics on the platform, and four tutorials cover it: extracting data from one project into another, connecting external tools with a manual connection string, the type and cast rules that trip up cross-source queries, and Metabase as a worked example.
PySpark handles the analysis that does not fit in a single query. The NYC taxi series works through a real public dataset in four parts, from one table to a multi-dataset comparison, and ends with a cheat sheet worth keeping open.
Two tutorials go further afield. AI Endpoints applies models to project data. OVHcloud billing analysis builds a cost dashboard from the OVHcloud API as a source, which doubles as a FinOps starting point.
Apache Superset covers the presentation layer: deploying it against a project, then two use cases built on top, FinOps reporting on FOCUS-format data and a sales dashboard for an online store.
Extract project data with Trino→
Move data from one project into another.
Integrating Trino with external tools→
Connect an external client with a manual connection string.
Trino data types and casts→
The mapping that causes most cross-source query errors.
Using Metabase with Trino→
A worked external-BI connection.
NYC taxi data analysis with PySpark→
A real public dataset in four parts, cheat sheet included.
Data analysis with AI Endpoints→
Apply models to project data.
OVHcloud billing data analysis→
Build a cost dashboard from the OVHcloud API.
Deploy Apache Superset→
Run Superset against a project.
FOCUS and Apache Superset use case→
FinOps reporting on FOCUS-format data.
Analyse online store sales→
Prepare two years of orders, then build a sales dashboard in Superset.
Go further
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