<p>Data is an incredible asset, especially when there are lots of it. Exploratory data analysis, business intelligence, and machine learning all depend on processing and analyzing Big Data at scale.</p> <p>How do you go from working on prototypes on your local machine, to handling messy data in production and at scale?</p> <p>This is a practical, hands-on course that shows you how to use Spark and it's Python API to create performant analytics with large-scale data. Don't reinvent the wheel, and wow your clients by building robust and responsible applications on Big Data.</p> <p>All the code and supporting files for this course are available on Github at -&nbsp;<a href="https://github.com/PacktPublishing/Hands-On-Pyspark-for-Big-Data-Analysis" target="_blank">https://github.com/PacktPublishing/Hands-On-Pyspark-for-Big-Data-Analysis</a></p> <h1>Style and Approach</h1> <p>This hands-on course is divided into clear bite-size chunks so you can learn at your own pace and focus on the areas of most interest to you. It’s practical and packed with step-by-step instructions, working examples, and helpful advice from our expert author. You will learn how PySpark provides an easy to use, performant way to do data analysis with Big Data.</p>