November 23-24



Jesse Anderson

Managing Director

Big Data Institute, Portugal


Jesse Anderson is a Data Engineer, Creative Engineer and Managing Director of Big Data Institute.

He trains at companies ranging from startups to Fortune 100 companies on Big Data. This includes training on cutting edge technology like Apache Kafka, Apache Hadoop and Apache Spark. He has taught thousands of students the skills to become Data Engineers.

He is widely regarded as an expert in the field and his novel teaching practices. Jesse is published on OReilly and Pragmatic Programmers. He has been covered in prestigious publications such as The Wall Street Journal, CNN, BBC, NPR, Engadget, and Wired.


Foundations of Data Teams

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 what management should do to fix it. To do this Jesse will be sharing a real-life analogy to show how we can be misled and what that means for our success rates.

We will talk about the teams in data teams: data science, data engineering, and operations. This will include detailing what each is, does, and the unique skills for the team. It will cover what happens when a team is missing and the effect on the other teams.

The analogy will come from his own experience with a house that had major cracks in the foundation. We were going to simply remodel the kitchen. We weren’t ever told about the cracks and the house needs a completely new foundation. In a similar way, most managers think adding in advanced analytics such as machine learning is a simple addition (remodel the kitchen). However, management isn’t ever told that you need all three data teams to do it right. Instead, management has to go all the way back to the foundation and fix it. If they don’t, the house (team) will crumble underneath the strain.

Session Keywords

🔑 Management
🔑 Teamwork
🔑 Data Science
🔑 Data Engineering

« Back