Analysis & statistics

BI workflow: turn raw tables into a model — without SQL

Working with operational and BI data from your databases? Define measures in a form, understand your joins in a read-only data model view, and define drill paths from coarse to fine — without a line of SQL.

DataLion Codebook → Business Intelligence: measures (SUM/COUNT/AVG), raw columns and drill paths in the Global Market Tracker project

DataLion turns raw database tables into a BI model — without SQL. You define measures (sum, count, average) in a form, promote raw columns to questions in one click, see your table joins in a read-only data model view, group raw data by a time grain, and define coarse-to-fine drill paths — the groundwork drill-down builds on.

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Measures as named aggregations

Define measures as named aggregations over the columns of your data tables — sum, count and average, for example "Total revenue = SUM(revenue)". You do this in a form, without writing any SQL.

Each measure is stored as a codebook entry, so it works immediately with the existing chart, filter, crosstab and export stack. The Global Market Tracker demo ships with measures like this already prepared.

  • Sum, count and average over table columns
  • Defined in a form, no hand-written SQL
  • Stored as a codebook entry — instantly usable in charts and export
  • Example: "Total revenue = SUM(revenue)"

A governed data model: raw columns and joins

The raw-columns panel shows which physical table columns have no codebook entry yet — with their detected type. "Promote to question" turns a single column into a regular codebook question in one click.

Your project's existing table joins render as a read-only data model view: each physical table is a card (the main table highlighted), each join is a table.column ⟷ table.column edge. When tables exist but no joins are defined yet, a hint points that out. You can also group any raw date by a time grain — minute, hour, day, week, month, quarter or year — via a column@grain reference (e.g. order_date@month), with no codebook entry. This works on MySQL and Exasol.

  • Raw-columns panel: unmapped columns with detected type
  • "Promote to question" turns a column into a question in one click
  • Read-only data model: table cards and join edges at a glance
  • Time grain via column@grain (minute to year), on MySQL and Exasol

Drill paths as hierarchy metadata

Define named, ordered hierarchies from coarse to fine in the codebook — for example Country → Region → City. DataLion validates the paths: the questions must exist, there need to be at least two distinct levels, and names are unique.

This is the hierarchy metadata layer that drill-down builds on. The Global Market Tracker demo ships drill paths alongside the matching measures and lookup tables, so you can see the whole thing work end to end.

  • Named, ordered hierarchies from coarse to fine
  • Example: Country → Region → City
  • Validated: existing questions, ≥ 2 levels, unique names
  • The groundwork drill-down builds on

See DataLion with your own data

Start free with your own raw data. Or book a personal demo of the path to a finished dashboard.

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We now work much more efficiently, giving us more time to take care of the derivations and insights from the data for the customers.
Jens Falkenau, Vice President of Market Research · Nielsen Sports
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More data features

Common questions about the BI workflow

Do I have to write SQL for measures?
No. You define measures as named aggregations — sum, count or average — in a form over the columns of your data tables, without writing SQL. They are stored as a codebook entry.
Which aggregations are available?
Sum, count and average. That lets you build measures like "Total revenue = SUM(revenue)". For more complex SQL expressions — such as NPS or indices — there are custom KPIs.
Can I edit the table joins visually?
The data model view is read-only: it shows your project's existing joins as table cards and table.column ⟷ table.column edges — ideal for understanding multi-table projects at a glance. It is not a drag-and-drop join builder.
How do I group raw data by time?
With a time grain: any raw date can be grouped by minute, hour, day, week, month, quarter or year via a column@grain reference — such as order_date@month — with no codebook entry. This works on MySQL and Exasol.
Are drill paths already a finished dashboard drill-down?
Drill paths are the named hierarchy metadata layer — ordered levels from coarse to fine, such as Country → Region → City, validated. You use them to define the groundwork that drill-down builds on.

Turn raw tables into a BI model

Try DataLion free: measures in a form, a governed data model and drill paths — without SQL. Or get a demo of the Global Market Tracker end to end.