Episode 130: Towards Accessible Data Analysis with Emanuel Zgraggen

Show Notes(01:59) Emanuel reflected on his upbringing in Switzerland and his 4-year apprenticeship in Software Engineering and Business at Credit Suisse.(06:09) Emanuel recalled his 4-year program in Computer Science at HSR (University of Applied Sciences Rapperswil).(08:43) Emanuel touched on his decision to pursue a Master’s degree at Brown University in the US.(11:58) Emanuel explained his decision to continue with a Ph.D. degree at Brown under the advisement of Professor Andy van Dam and summarized the arc of his Ph.D. research focus.(14:50) Emanuel highlighted his first research paper called PanoramicData on Interactive Data Exploration.(16:42) Emanuel shared his thoughts on common traits of a successful researcher.(18:03) Emanuel emphasized the focus of his research at the intersection of Human-Computer Interaction, Information Visualization, and Data Analysis.(20:38) Emanuel shared valuable lessons from interning twice at Microsoft Research in Redmond.(22:34) Emanuel talked about his time as a postdoc in Professor Tim Kraska’s group at the CSAIL at MIT.(24:59) Emanuel shared the founding story of Einblick - a visual computing platform that enables data teams to answer tougher, more meaningful questions by making advanced analytics and model building more streamlined and accessible.(29:06) Emanuel touched on the responsibilities of Einblick's 5 co-founders.(30:23) Emanuel highlighted technical challenges of building Einblick's integrated environment for descriptive, predictive, and prescriptive analytics.(32:09) Emanuel mentioned the collaboration challenge in data and brought up Einblick's real-time remote collaboration through video-enabled data whiteboards.(35:39) Emanuel highlighted the challenges of working with computational notebooks and brought up the benefits of using Einblick's collaborative visual canvas.(38:54) Emanuel unpacked the challenges of commercializing an academic research project.(40:27) Emanuel gave a broad overview of Einblick's go-to-market strategy.(43:55) Emanuel shared valuable hiring lessons to attract the right people who are aligned with Einblick’s cultural values.(47:05) Emanuel shared fundraising advice to founders who are seeking the right investors for their startups.(49:20) Emanuel shared the similarities and differences between being a researcher and being a founder.(50:43) Closing segment.Emanuel's Contact InfoWebsiteGoogle ScholarLinkedInTwitterEinblick's ResourcesWebsite | Twitter | LinkedInDocs | BlogChartGen AINotebook Feature Release (2022)Video-Based Collaboration Release (2021)Mentioned ContentPapers and ProjectsPanoramicData is a hybrid pen and touch system for visual data exploration (Infovis 2014 Paper | Video)(s|qu)eries (pronounced “Squeries”) is a visual query interface for creating queries on sequences (series) of data based on regular expressions (CHI 2015 Paper | Summary Video)Vizdom is an interactive visual analytics system that scales to large datasets through progressive computation (VLDB Demo 2015 Paper | Health Video | Election Video)Tableur is a spreadsheet-like pen- and touch-based system that revolves around handwriting recognition - all data is represented as digital ink (CHI 2016 LBW Paper | Video)Towards Accessible Data Analysis (Emanuel's Ph.D. Dissertation at Brown, 2018)Northstar is an interactive data science platform that combines data exploration with automated machine learning (SIGMOD DEEM Paper | Video)PeopleWes McKinneyFei-Fei LiBooks"The Book of Why" (by Judea Pearl)"The Signal and The Noise" (by Nate Silver)Notes

My conversation with Emanuel was recorded back in late 2022. Since then, I recommend checking out the launch of Einblick Prompt and ChartGenAI.

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.