Over the past few decades, we’ve experienced the benefits of centralizing data into data warehouses, lakes, and now lakehouses. We’ve also made progress around “democratizing data” by pushing data literacy and giving more people access to more data (usually through BI tools).
Now the question is, can we free analytics from the confines of BI tools and let data radiate throughout more applications, workflows, and daily processes? In this talk, we’ll explore how organizations can go beyond being internally “data-driven” and take a more active stance to enable customers, partners, and internal processes by surfacing interactive analytics into the existing tools they’re already using.
Maxime Beauchemin recently joined Lyft as a Software Engineer after some time at Airbnb as a data engineer developing tools to help streamline and automate data engineering processes. He is also the creator and lead committer on Apache Airflow and Apache Superset. He mastered his data warehousing fundamentals at Ubisoft and was an early adopter of Hadoop/Pig while at Yahoo in 2007. More recently, while at Facebook, he developed analytics-as-a-service frameworks around engagement and growth metrics computation, anomaly detection, and cohort analysis. He’s a father of three, and in his free time he’s a digital artist.