Presented By O'Reilly and Cloudera
Make Data Work
March 13–14, 2017: Training
March 14–16, 2017: Tutorials & Conference
San Jose, CA

In-Person Training
Real-time data engineering in the cloud

Jesse Anderson (Big Data Institute)
Monday, March 13 & Tuesday, March 14, 9:00am - 5:00pm
Secondary topics:  Architecture, Cloud
Average rating: ****.
(4.00, 1 rating)

Participants should plan to attend both days of this 2-day training course. Platinum and Training passes do not include access to tutorials on Tuesday.

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.

What you'll learn, and how you can apply it

  • Explore the latest real-time frameworks and the leading cloud providers
  • Discover how to choose the right open source technology or managed cloud service for your company
  • Learn how to create real-time data pipelines using the latest open source and managed cloud services, ingest data in real time and at scale, process the data once you've ingested it, and create data products from real-time data sources

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.

About your instructor

Photo of Jesse Anderson

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.

Twitter for jessetanderson

Conference registration

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Comments

Picture of Jesse Anderson
Jesse Anderson | MANAGING DIRECTOR
02/24/2017 12:15am PST

I created a demo of the final exercise. This shows how we’re bringing everything together, analyzing it, and visualizing it.

Picture of Jesse Anderson
Jesse Anderson | MANAGING DIRECTOR
02/24/2017 12:13am PST

This will be applicable to both private, hybrid, and public cloud environments. We’ll be focusing on Apache Kafka and Apache Spark which are open source and aren’t specific to any cloud provider. Hope to see you there!

William Thompson | TECHNICAL LEAD
02/23/2017 11:52pm PST

Will this be applicable to Private and Hybrid cloud environments or mostly focused on Public cloud deployment?

Picture of Jesse Anderson
Jesse Anderson | MANAGING DIRECTOR
01/17/2017 9:03am PST

This isn’t a beginning Big Data course. You will need to know that coming in. You will need Java skills. This course is aimed at Data Engineers, Software Engineers, Big Data Engineers, DevOps Engineers, and Software Architects.

There are extensive labs. The course itself is about 50% lecture and 50% labs. One of the final labs will be to use a cluster in the cloud to process data.

Sonali Gupta | AVP PRODUCT DEVELOPMENT
01/16/2017 11:10am PST

I have a question about this training module. What are the prerequisites recommended to be able to make the most of this course? What sort of profile is the intended audience? Does this training have lab sessions as well as lectures?