Data & codebook
- Generate a codebook automatically
With a structured and labeled dataset, you can generate the codebook automatically for faster results and no manual work.
- The Codebook - Part 1
What is a codebook and why do I need one? The codebook contains all the key instructions and criteria used to link your data with DataLion.
- The Codebook - Part 2
The codebook is a metadata file that defines the default settings of a project and links the dataset with DataLion, so data can be visualized easily.
- SQL calculations
Use SQL commands in the codebook and in source-code text fields to calculate sums, means, shares and KPIs, and to define SQL filters.
- Handling missing values
How to define which values count as missing in DataLion, whether they enter percentages and means, and how to show them as their own "No answer" category.
- Zero-downtime update (automatic)
With the zero-downtime update, data in a project can be uploaded automatically without the dashboard being temporarily unavailable because of the data upload.
- Data sources and data tables
Data is uploaded into DataLion via the project backend into data sources. As soon as a data source is filled with data, a corresponding data table is created in the database.
- Zero-downtime update (manual)
An (almost) zero-downtime update can be carried out manually, so that data in a project can be uploaded with the dashboard being unavailable for only a very short time.
- Data updates
How to update data in DataLion – including automatic and manual zero-downtime updates, so that dashboards remain accessible during the process.
- Manage tracker waves
How to set up waves for recurring studies in DataLion, maintain field periods and status, compare with the previous wave automatically and export single waves.
- Upload new waves without duplicating data
How to upload new waves to DataLion: partition key, what happens to waves already in the table, excluding columns and the update with release.
- Using (multiple) data sources in one project
DataLion lets you use one or more data sources in a project and, if needed, link them together (join). Here is how to set this up.
- Check project health
The Health page finds formula errors, unknown columns, wrong values and failed charts in a DataLion project. How to read and fix each finding.
- Calculate the Net Promoter Score (NPS)
Codebook formulas for the NPS from an eleven-point scale: the long version that excludes missing values, a short version, and the weighted variant.