Or, why science and engineering are still different disciplines.
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.
Getting DataOps right is crucial to your late-stage big data projects.
Poll results reveal where and why organizations choose to use containers, cloud platforms, and data pipelines.
The two positions are not interchangeable—and misperceptions of their roles can hurt teams and compromise productivity.
Learn to identify problems that may indicate data team dysfunction.
Learn some of the benefits of using real-time processing of data for some use cases.
Practical questions to help you make a decision.
Merging the gaps between data science and engineering, and what each side can learn from the other.
Why big data isn’t easy, cheap, or quick.
Using Apache Beam to become data-driven, even before you have big data.
A business leader’s guide to beginning the big data journey.
Jesse Anderson will show you how to recognize the opportunities, avoid the problems, and get the most value from your data.