Time Series Analysis with Spark
A practical guide to processing, modeling, and forecasting time series with Apache Spark
Created by Yoni Ramaswami
Explore practical techniques for analyzing, modeling, and forecasting time series data using Apache Spark and Databricks. Learn how to handle large-scale datasets, build scalable models, and apply advanced tools like Generative AI to real-world challenges. Gain hands-on experience that prepares you for modern data-driven projects.
Packt | Mar 2025 | 298 min
What You Will Learn
You will start by learning foundational concepts of time series analysis and how Spark's distributed computing makes large-scale processing efficient. Through practical examples and industry use cases, you will practice preparing data, building models, and deploying solutions. Advanced topics like Generative AI and production workflows are included to deepen your expertise.
Key Features
- Build and train scalable time series models using Apache Spark and Databricks
- Apply best practices for preparing, processing, and deploying time series solutions
- Use Generative AI to enhance forecasts and uncover valuable patterns in your data
Target Audience
Ideal for data engineers, ML engineers, data scientists, and analysts who want to strengthen their time series analysis skills using Spark and Databricks. If you have a basic understanding of Spark and want to apply it to real-world forecasting and analytics, you will find actionable techniques and insights to advance your projects.
