Overview of Mapper

Introduction to Mapper

Mapper is one of elluminate’s options for transforming imported data into new tables or domains and delivering it to a target data store. Mapper provides a graphical interface to perform complex transformations in a low-code environment while the platform generates T-SQL.

Important: Mapper transformations and outputs respect user privileges and Data Blinding rules. If the user or execution account has the Blinded Data View privilege, unblinded values may be used in transformations and included in derived outputs. Verify that access privileges align with the study’s blinding strategy when working with sensitive data.

Why Use Mapper

Assists with transforming imported data to CDISC (e.g., SDTM or ADaM), DMOD, custom standards, or listings to support reporting and analytics.
Links to Standards and Specifications, providing auto-complete field names, labels, and code lists to reduce errors.
Reuses work across studies by exporting or promoting mapped domains to the Global Library for import elsewhere in elluminate.
Tracks versions, execution history, and data dependencies to support transparency and reproducibility.

Mapper provides a Domain Editor that displays source tables, transformation layers, and previews of data or SQL. Property panels support domain and variable configuration, along with tools for importing, exporting, migrating, and scheduling mappings.

Key Features Include

Dynamic Unions: Combine multiple tables that follow a naming pattern into a single domain without requiring manual unions.
SQL Tokens: Replace hard-coded schema prefixes to make code portable across studies and environments.
Skip Missing / Cascade Changes: This option allows mappings to run even when variables or domains are absent and propagates edits through parent layers when desired.
Global Library Integration: Promotes mapped domains to the Global Library for cross-study reuse governed by user privileges.

Access Mapper

From the Platform Menu, select Mapper from Data Mapping & Computing.
From the right side of the Platform Menu, select a study. The Mapper window opens.
Note: If a Global Data Store is used for the mapping, select Global Data Stores (instead of Studies) from the Platform menu. Then, choose the data store and select Mapper from the module drop-down, which defaults to Details.

The top half of the window displays any existing Mappings. A mapping is a set of domains or tables created from the source domains or data imported into the study.

The bottom half of the window displays the corresponding Domains after a mapping is selected from the top half of the window.

Domain Transformation Options

OPTION		DESCRIPTION
Variable Rules	General	Define exclusions, rename variables, convert data types, or derive variables.
	Filtering	Set filter rules to control which data is mapped.
	Sorting	Set the sort order for mapped data.
	Pivot / Unpivot	Transform data between row-based and column-based structures.
	Aggregate / Rank	Calculate summary values or assign ranking and sequencing within a dataset.
Domain Rules	Join	Combine data from multiple tables by defining join conditions to create a new table with columns from each source table.
	Union	Combine rows from two tables. Requires both tables to have the same number of fields and compatible structure.
	Dynamic Union	Combine rows from multiple tables into a single transformation based on defined criteria.
	Intersect	Return only records that exist in both tables.
	Subtract	Return records from the first table that do not exist in the second table.