Episode 114: Building Data Products and Unlocking Data Insights with Carlos Aguilar

Show Notes(02:06) Carlos shared formative experiences of his upbringing tinkering with robots and websites.(04:03) Carlos reflected on his education, studying Mechanical and Aerospace Engineering at Cornell University.(05:34) Carlos discussed the technical details of his research on machine learning applications in robotics and art.(10:11) Carlos explained his work as a robotic system analyst at Kiva Systems.(15:41) Carlos discussed building his first data product at Kiva.(20:24) Carlos recalled his stint working on warehouse-automating distributed robots at Amazon Robotics (after the Kiva acquisition).(24:31) Carlos revealed his decision in 2013 to join an early-stage healthcare startup called Flatiron Health as the first data hire.(28:43) Carlos shared his experience building Flatiron's Data Insights team from scratch.(31:51) Carlos reviewed different data products built and deployed at Flatiron Health.(38:41) Carlos shared the key learnings from hiring for his data team at Flatiron.(44:08) Carlos shared the founding story of Glean, which is building a new way to make data exploration and visualization accessible to everyone.(50:52) Carlos explained the pain points in data visualization/exploration and the product features of Glean that address them.(55:03) Carlos dissected Glean DataOps, which brings modern developer workflow to the business intelligence layer and prevents broken dashboards.(59:28) Carlos outlined the long-term product vision for Glean.(01:03:11) Carlos shared valuable hiring lessons to attract the right people who are excited about Glean's mission.(01:07:15) Carlos discussed his team's challenges in finding the early design partners.(01:10:13) Carlos shared fundraising advice to founders who are seeking the right investors for their startups.(01:11:57) Closing segment.Carlos' Contact InfoTwitterLinkedInGitHubWebsiteMediumGlean's ResourcesWebsite | Twitter | LinkedInAbout | Docs | BlogInteractive Public Demo | DataOpsMentioned ContentBlog PostsHow the Data Insights team helps Flatiron build useful data products (May 2018)The biggest mistake making your first data hire: not interviewing for product (July 2020)How to interview your first data hire (Aug 2020)My hack for getting started with data as a product (May 2021)Introducing Glean (March 2022)Your dashboard is probably broken (April 2022)PeopleVicki BoykisAnthony GoldbloomWes McKinneyBookThe Toyota Way: 14 Management Principles from the World's Greatest Manufacturer (by Jeffrey Liker)Notes

My conversation with Carlos was recorded back in June 2022. The Glean team has had some announcements in 2023 that I recommend looking at:

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email [email protected].

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.

Datacast features long-form, in-depth conversations with practitioners and researchers in the data community to walk through their professional journeys and unpack the lessons learned along the way. I invite guests coming from a wide range of career paths — from scientists and analysts to founders and investors — to analyze the case for using data in the real world and extract their mental models (“the WHY and the HOW”) behind their pursuits. Hopefully, these conversations can serve as valuable tools for early-stage data professionals as they navigate their own careers in the exciting data universe.

Datacast is produced and edited by James Le. For inquiries about sponsoring the podcast, email [email protected].

Subscribe by searching for Datacast wherever you get podcasts, or click one of the links below:

If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.