Introduction

This section provides a set of self-study materials focused on performance in Analytics, Dashboards and Price Setting.

✅Learning Prerequisites

To understand this learning path you must have at least basic knowledge of:

• Groovy

• IntelliJ

• Pricefx Studio

🧭 Learning Synopsis

Upon completing this path, you will have gain a deeper understanding of performance in the most commonly used capabilities within the software and you will be able so solve selected use cases that apply.

The learning content covers critical performance practices for analytics systems. You will understand strategies for managing data volumes, optimizing data loading techniques, and leveraging throttling mechanisms. Key focuses include efficient data querying through aggregation and filtering, as well as leveraging database-level joins. Additionally, we focus on optimizing data querying and caching, utilizing distributed calculations, and setting appropriate default sorting preferences to take advantage of database indexes.

🎯 Learning Objectives

For this learning path these are the core topics and takeaways:

• Implement data volume management strategies to prevent unbounded growth in analytics systems.

• Optimize data loading approaches to improve performance for header-level and row-level loads.

• Monitor and configure throttling mechanisms to maintain high query performance in analytics.

• Understand the execution model of dashboard logic and its implications for performance optimization.

• Apply best practices for efficient data querying, including aggregation and effective filtering.

• Recognize the benefits of database-level joins over Groovy-based joins for improved dashboard performance.

• Develop strategies to address the impact of data growth on dashboard performance over time.

• Manage data volumes and growth in price grids and price lists effectively.

• Optimize querying and caching of data to improve performance.

• Configure UI and database settings to leverage indexing and distributed calculations.

🚘 Learning Journey

This learning path is divided into distinct tracks. This structured approach ensures that learners have the necessary foundation before progressing to more advanced concepts, optimizing the learning experience and maximizing the effectiveness of your learning:

This learning path will cover the following topics. Make sure you go through them in order to build a solid knowledge foundation.

• Performance Practices in Analytics

• Performance Practices in Dashboards

• Performance Practices in Price Setting

⏲️ Time commitment: For this path you should dedicate approximately 2 hours.