The Data Transformation Language (DTL) is InfoSum's custom scripting language, which can help you map your original data format onto InfoSum's Global Schema. If you haven't read them already, our glossary topics on normalisation and transformations will explain more about the role of DTL and the requirement to transform your data.
Many transformations can be configured using your bunker's user interface, without the need to write or understand DTL. For more advanced requirements, however, DTL offers a powerful tool to apply complex logic to your transformations.
DTL is an advanced technique. Before you decide to write a DTL script, check whether other features in your bunker - such as mappings - might be enough to meet your needs.
How to learn DTL
First, read our Quick Start articles, which bring you up to speed on the key principles of DTL.
- Bunker and the Script Editor explains where DTL fits in the overall process of importing and normalising your data, and how you can write a DTL script inside your bunker.
- Language essentials gives a run-down of DTL's syntax, and how it's similar to and different from other scripting languages you may have used.
- Three rules to remember outlines three important principles for the output of your DTL scripts, which you'll need to follow as you transform your data.
You'll then be ready to check out our tutorials - which talk you through some of DTL's main features using practical, real-world examples.
- Rewriting a column using string functions shows you how to write a simple DTL script to change the value of a column, and introduces some useful string-handling functions provided by DTL.
- Combining data from multiple columns shows you how to use DTL to combine several columns from your original data into one category in InfoSum's Global Schema.
- Applying regular expressions using
match_regexexplains how to use DTL's most powerful feature, analysing and rewriting data using regular expressions.
Finally, two reference articles provide technical detail on the DTL language.