Welcome
Administration
Learn about how to configure, manage, and maintain HCL Detect environments. It includes details on system setup, user management, and permissions, ensuring seamless operation and efficient deployment of your continuous delivery processes.
About derived attribute functions
Derived attribute functions enable you to offload complex calculations involving multiple tuple attributes to custom Python scripts.

Getting Started
Welcome to the documentation for HCL Detect, where you can find information about how to install, maintain, and use this service.
Installation
Learn more about HCL Detect installation and deploying core components of the product.
Administration
Learn about how to configure, manage, and maintain HCL Detect environments. It includes details on system setup, user management, and permissions, ensuring seamless operation and efficient deployment of your continuous delivery processes.
- Introduction
  Use this guide to administer HCL Detect, including user and role access, CLI-based configuration and management tasks, DEL reference topics, and support resources.
- User & Role Management
  This page explains how to manage roles and permission in HCL Detect.
- Configuration Management
  Use CLI commands to query and validate the infrastructure settings required for Detect operations.
- Metadata Management
  Use CLI commands to discover data sources, search tables, and retrieve column metadata for Detect integrations.
- Profile Management
  Manage profile definitions and attributes through the HCL Detect UI or CLI.
- Feed Application
  Create and manage feed applications through the HCL Detect UI or CLI.
- About derived attribute functions
  Derived attribute functions enable you to offload complex calculations involving multiple tuple attributes to custom Python scripts.
  - Implement Python script and JSON configuration
    Define your custom business logic in a Python script and expose it to the Detect UI using a JSON configuration file.
  - Configure derived attribute functions in the feed application
    Apply custom Python logic to your data streams by configuring the derived attribute in the feed management UI.
  - Configure derived attribute functions in the pipeline
    Incorporate the configured derived attribute into your active pipeline for data processing.
- Feed Parser Mapping
  Use CLI commands to define and maintain feed parser mappings between incoming feed fields and Detect target attributes.
- Destination Management
  Use CLI commands to configure, validate, and manage destination endpoints for Detect event delivery.
- Crypto Management
  Use CLI crypto utilities to encrypt and decrypt sensitive values used in Detect configuration workflows.
- Troubleshooting & Common Errors
- Detect Expression Language
- Detect Expression Language Built-in Functions
Working with the System
The section provides comprehensive instructions for creating, configuring, and managing marketing events. It covers topics such as defining audience conditions, setting up triggers, deploying events, and tracking their performance. Additionally, this section includes explanations of key terminology and offers advanced options to optimize event management.
System Data Model
This section provides detailed information about the internal tables used within the Detect module. It includes descriptions of each table's structure, purpose, and relationships, aiding administrators and developers in understanding and managing the underlying database schema effectively.

About derived attribute functions

Derived attribute functions enable you to offload complex calculations involving multiple tuple attributes to custom Python scripts.

Use derived attribute functions when you need to execute complex business logic that standard engine computations can't handle efficiently. By passing tuple data to a dedicated Python function, the system calculates the result and returns the value to the engine.

A typical use case involves financial computations. For example, calculating a final transaction amount based on varying geographic tax rates and surcharges.

To implement a derived attribute function, administrators must configure two primary components:

Python Script: Contains the core logic to process the tuple attributes and return a double value.
JSON Definition: Defines the function signature, expected inputs, and variables so that the function is available in the Detect user interface.

Store back mechanism

The store back feature allows the system to save a computed value from a current processing event (a tuple) into a database. This ensures the value is remembered and can be retrieved when future tuples arrive for the same entity.

The system uses a key identifier (such as an audience key) to store the computed value into a designated column within a store back table.

For example, consider a scenario where you want to track customer information across different events:

A tuple arrives with audience ID 123.
The system calculates a value (for example, an updated transaction total of 456).
The store back function saves the value 456 in a designated column (for example, a zip code column) for audience ID 123 in the designated lookup table.
When a subsequent tuple arrives for audience ID 123, that saved value is available for retrieval.