PySpark Training in Sud-Vest

Stratio is a data-centric platform that combines big data, artificial intelligence, and governance into a unified solution. Its Rocket and Intelligence modules facilitate rapid data exploration, transformation, and advanced analytics within enterprise settings.

This instructor-led training session, available both online and on-site, is designed for data professionals at an intermediate level who aim to effectively utilize Stratio's Rocket and Intelligence modules with PySpark. The curriculum focuses on looping structures, user-defined functions, and complex data logic.

Upon completing this training, participants will be capable of:

• Navigating and operating within the Stratio platform using the Rocket and Intelligence modules.
• Applying PySpark for data ingestion, transformation, and analysis.
• Utilizing loops and conditional logic to manage data workflows and feature engineering tasks.
• Creating and managing user-defined functions (UDFs) to enable reusable data operations in PySpark.

Format of the Course

• Interactive lectures and discussions.
• Extensive exercises and practical practice.
• Hands-on implementation within a live-lab environment.

Course Customization Options

• To request customized training for this course, please contact us to arrange.

In this instructor-led, live training in Sud-Vest, participants will learn how to use Python and Spark together to analyze big data as they work on hands-on exercises.

By the end of this training, participants will be able to:

• Learn how to use Spark with Python to analyze Big Data.
• Work on exercises that mimic real world cases.
• Use different tools and techniques for big data analysis using PySpark.

This instructor-led live training (online or onsite) targets data engineers, data analysts, and data professionals who aim to use Databricks and PySpark to build scalable data pipelines and migrate existing SQL workflows.

This course offers a hands-on introduction to developing scalable data processing and Machine Learning workflows using PySpark. Participants will discover how Apache Spark functions within contemporary Big Data ecosystems and learn to process large datasets efficiently by leveraging distributed computing principles.