Software Architectures

What I Learned From Attending Tecton's apply() Conference

What I Learned From Attending Tecton's apply() Conference

Last week, I attended apply(), Tecton’s first-ever conference that brought together industry thought leaders and practitioners from over 30 organizations to share and discuss ML data engineering’s current and future state. The complexity of ML data engineering is the most significant barrier between most data teams and transforming their applications and user experiences with operational ML.


In this long-form blog recap, I will dissect content from 23 sessions and lightning talks that I found most useful from attending apply(). These talks cover everything from the rise of feature stores and the evolution of MLOps, to novel techniques and scalable platform design. Let’s dive in!

Datacast Episode 54: Information Retrieval Research, Data Science For Space Missions, and Open-Source Software with Chris Mattmann

Datacast Episode 54: Information Retrieval Research, Data Science For Space Missions, and Open-Source Software with Chris Mattmann

Chris Mattmann is the Chief Technology and Innovation Officer at NASA JPL. He is also JPL's first Principal Scientist in the area of Data Science. He has over 19 years of experience at JPL and has conceived, realized, and delivered the architecture for the next generation of reusable science data processing systems for NASA's space and earth science missions.

He contributes to open source and was a former Director at the Apache Software Foundation (2013-18).

Finally, he is the Director of the Information Retrieval & Data Science (IRDS) group at USC and Adjunct Associate Professor.