This comprehensive tutorial will acquaint you with all the aspects of real-time analytics with Apache Spark, one of the trending Big Data processing frameworks on the market today. It will show you how to leverage the features of various components of the Spark framework to efficiently process, analyze, and visualize your data. You will learn how to implement the high velocity streaming operation for data processing in order to perform efficient analytics on your real-time data. You'll analyze data using machine learning techniques and graphs. You'll learn about Spark Streaming and create real-world streaming processing that address all the problems that need to be solved. You'll solve problems using Machine Learning techniques and find out about all the tools available in the MLlibtoolkit. You'll find out how to leverage Graphs to solve real-world problems. At the end of this video, you'll also see some useful Machine Learning algorithms with the help of Spark MLlib and will integrate Spark with R. We'll also make sure you're confident and prepared for graph processing, as you'll learn more about the GraphX API. By the end, you'll be well-versed in the aspects of real-time analytics and implement them with Apache Spark. Style and Approach.Filled with hands-on examples, this course will help you perform data analysis and take you from an intermediate level to an advanced approach to data analytics. You will perform graph analysis, handling high velocity streaming with some analytical use cases.
This course is for aspiring big data analysts and data scientists looking for a deep dive in graphical processing and advanced analytics of data processing. You are required to have an initial understanding of Spark Programming and the fundamentals of Apache Spark along with some basic understanding of real-time data processing.