Real-time big data frameworks are enabling brand-new use cases, while the cloud is letting us do things cheaper and faster than ever. Together, they’re making it easier to create production real-time systems. But to handle real-time big data, you need to solve two difficult problems: how do you ingest that much data and how will you process that much data?
Jesse Anderson explores the latest real-time frameworks (both open source and managed cloud services), discusses the leading cloud providers, and explains how to choose the right one for your company. Focusing on Apache Kafka and Apache Spark, Jesse also demonstrates how to ingest data, process it, analyze it, and display it in real time with a dashboard.
For the final exercise, you’ll take data that has been ingested with Kafka and process it with Spark Streaming and visualize it on a web page with D3. This video gives a little more information about the final exercise so you can see the skills you’ll take away from the class.
"Deep dive in Spark streaming, lots of content, not for the faint of heart." – Patrick Paul
"This class provided a lot of insight into real-time data engineering and integration into the cloud. It introduced technologies that I was unaware of. Jesse Anderson was very knowledgeable and presented the material very clearly and addressed all questions." – Richard Chabanne
Jesse Anderson is a data engineer, creative engineer, and managing director of the Big Data Institute. Jesse trains employees on big data—including cutting-edge technology like Apache Kafka, Apache Hadoop, and Apache Spark. He has taught thousands of students at companies ranging from startups to Fortune 100 companies the skills to become data engineers. He is widely regarded as an expert in the field and recognized for his novel teaching practices. Jesse is published by O’Reilly and Pragmatic Programmers and has been covered in such prestigious media outlets as the Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired. You can learn more about Jesse at Jesse-Anderson.com.
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