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User Defined Analytics Overview

Introduction

This section provides an overview of User Defined Analytics (UDAs) and their role within the kdb Insights environment. UDAs allow you to create custom analytics that are tailored to your specific needs, enabling you to extend the capabilities of kdb Insights beyond its standard functionality.

Why Use UDAs?

UDAs are a valuable tool within kdb Insights because they allow you to:

  • Tailor solutions - Address specific analytical needs that standard tools may not fully support.

  • Integrate complex logic - Implement complex business logic within your analytics workflows, ensuring that your analysis meets precise requirements.

  • Streamline processes - Automate and simplify repetitive analytical tasks by using them within reusable UDAs.

Benefits

Some of the advantages of using UDAs in your kdb Insights projects:

  • Enhanced customization - UDAs allow you to create analytics that are specifically designed for your unique business requirements.

  • Performance optimization - By tailoring UDAs to your data and use cases, you can achieve optimal performance in data processing and analysis.

  • Reusability - Once created, UDAs can be reused across multiple projects, saving time and ensuring consistency in your analytical processes.

Getting Started

To begin using UDAs, follow these steps:

  1. Understand the basics - Familiarize yourself with what UDAs are and how they integrate with kdb Insights.

  2. Create your first UDA - Learn how to build a UDA, incorporating your custom logic and testing it within the kdb Insights environment.

  3. Package your UDA - Once your UDA is ready, package it with the necessary configuration and metadata for deployment.

  4. Deploy your UDA - Deploy your UDA to make it available for use within your kdb Insights environment. Validate the deployment to ensure everything is functioning correctly.