Jesse Anderson
Data Engineer, Creative Engineer and Managing Director
Big Data Institute
Jesse Anderson is a Data Engineer, Creative Engineer and Managing Director of Big Data Institute. He mentors companies all over the world ranging from startups to Fortune 100 companies on Big Data. This includes projects using cutting-edge technologies like Apache Kafka, Apache Hadoop, and Apache Spark. He is widely regarded as an expert in the field and for his novel teaching practices. Jesse is published on Apress, O’Reilly, and Pragmatic Programmers. He has been covered in prestigious publications such as The Wall Street Journal, Harvard Business Review, CNN, BBC, NPR, Engadget, and Wired. You can learn more about Jesse at Jesse-Anderson.com.
Talks I've Given
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Why Most Data Projects Fail and How to Avoid It
Featuring Jesse Anderson
Unfortunately, the majority of data projects fail. Yet, they fail for the same reasons. Most management and data teams don’t know the reasons a project succeeds or fails. It just appears to be random, hard work, or luck.
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Foundations of Data Teams
Featuring Jesse Anderson
Successful data projects are built on solid foundations. What happens when we’re misled or unaware of what a solid foundation for data teams means? When a data team is missing or understaffed, the entire project is at risk of failure.
This talk will cover the importance of a solid foundation and...
data-science -
Creating a Data Engineering Culture
Featuring Jesse Anderson
At this month's Data Matters, we're excited to be joined by Jesse Anderson! Jesse will share the stories of teams who haven’t set up their data engineering culture correctly and what happened, and how to turn it around. Don't miss it!
data data-practices good-practie data-management bigdata data-engineering -
Keynote: Why Real-Time is the Future
Featuring Jesse Anderson
Real-time Big Data systems are making previously impossible use cases possible. This talk will cover some of the limitations with batch Big Data systems. Then, we will talk about the use cases that real-time systems enable and the sorts of technologies used in them. Finally, we will talk about...
infiniteconf datascience data data-engineering -
Processing Data of Any Size with Apache Beam
Featuring Jesse Anderson
Rewriting code as you scale is a terrible waste of time. You have perfectly working code, but it doesn’t scale. You really need code that works at any size, whether that’s a megabyte or a terabyte. Beam allows you to learn a single API and process data as it grows. You don’t...
data