Big Data Visualization For Games Using Elastic Stack

[lesedev317]

Big Data Visualization For Games Using Elastic Stack
Published 2/2025
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 3.27 GB | Duration: 4h 16m
Learn how to generate, process, and visualize Game Dev logs using Elastic Stack with an example of Unreal Engine 5​

What you'll learn
Learn how to generate, process and analyze logs created during the game development process with Elastic Stack
Utilize Elastic stack (Elasticsearch, Logstash, Kibana) to process game development logs
Build Kibana Dashboard with insightful widgets representing Session, Location and Performance game data
Integrate Unreal Engine 5 Game World map to Kibana Visualization
Use Python to interact with Elasticsearch
Requirements
Skills: No previous experience in the field required
Tools: Elastic Stack, Unreal Engine 5, Python, VS Code. All have free access.
Description
Welcome to Big Data Visualization for Games using Elastic Stack!This course is your gateway to mastering data-driven insights for game development using the Elastic Stack (ELK).Whether you're a Data Analyst, QA Engineer, Tech Lead, Pipeline Architect, Automation/DevOps Engineer, or a Tech Artist, this course is designed to equip you with the practical skills to process, analyze, and visualize game data for improved development workflows and decision-making.What You'll LearnThroughout the course, you'll explore and implement Big Data visualization solutions, covering three essential types of game development logs:Game Session Data: Track who played the game, for how long, and on which platform, providing insights and foundation for more specific metrics, like Crash-per-hour rate, average play session durations, etc.Performance Data: Analyze historical Performance metrics (FPS, CPU/GPU usage, memory consumption, function execution times) across different builds, platforms, and gameplay scenarios to make informed decisions in performance optimizations.Location-Specific Data: Recreate player movement path, map game crashes, rare boss kills, FPS dropped, and other key events using interactive game maps in Kibana.By the end of this course, you'll have a fully functional Big Data dashboard that transforms raw logs into actionable insights!This course is fully practical (similar to my Python-related courses) where most of the time you're attending workshops with various challenges rather just watching raw-slides lectures. As a source of our game logs throughout the course we will be using Unreal Engine 5 with its Sample Project Stack-O-Bot to mimic the real-world data and meaningful metrics for analysis.All the tools involved in the course content have Free access.Source Code included.
Data Analysts,Quality Assurance, DevOps, Automation Engineers,Technical/Pipeline Directors,Tools programmers,Technical Artists
Screenshot

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