Transformation

About Transformations →

An overview of all transformations in ETLBox

This article will give you an overview of all transformations that currently exist in ETLBox. If you already know what kind of transformation you are looking for, you can visit directly the article that goes more into the details.

Caching Rows →

Details about the CachedRowTransformation

The CachedRowTransformation does basically the same as the RowTransformation, but has a cache to access previously processed data rows.

Column Rename →

Details about the ColumnRename

This transformation let you rename the properties names of your ingoing data. Also, you can remove columns from your flow.

Distinct →

Guide to Using the Distinct transformation

Efficiently filter out duplicate records with the Distinct transformation.

Filter Transformation →

Details about the FilterTransformation

The FilterTransformation filters out row that do not match with a given predicate.

Lookup →

Details about the LookupTransformation

If you want to lookup some data from existing tables or other sources, the lookup transformation is the right choice. It allows you to enrich the incoming rows with data from the lookup source.

Merge Join →

Details about the MergeJoin

The MergeJoin transformation joins the outcome of two sources or transformations into one data record. This allows you to merge the data of two inputs into one output.

Multicast (Broadcast) →

Details about the Multicast

The Multicast is a component which basically clones your data and send them to all connected target. It has one input and can have two or more outputs.

Row Duplication →

Details about the RowDuplication

The RowDuplication simply creates duplicates of the incoming rows. You can specify how many copies you want or if you want to create a copy only if a predicate evaluates to true.

Row Multiplication →

Details about the RowMultiplication

The RowMultiplication allows to create multiple records out of one input record. It works like a RowTransformation - so it accepts an input and an output type - but instead of just modifying one records it can return an array of records (when you return an empty list, it will even remove the incoming row).

Row Transformation →

Details about the RowTransformation

The RowTransformation will apply a custom transformation function to each row of incoming data. This transformation is useful in many scenarios, as it allows you to apply any .NET code to your data.

Xml Schema Validation →

Details about the XmlSchemaValidation

This transformation allows you to validate XML code in your incoming data against a XML schema definition.