Episode 85: Ad Exchange, Stream Processing, and Data Discovery Platform with Shinji Kim
Datacast
English - March 02, 2022 07:00 - 1 hour - 65.1 MB - ★★★★★ - 4 ratingsTechnology Business Careers research data engineering data science artificial intelligence machine learning statistics technology startup computer science venture capital Homepage Download Apple Podcasts Google Podcasts Overcast Castro Pocket Casts RSS feed
Show Notes(02:00) Shinji reflected on her academic experience studying Software Engineering at the University of Waterloo in the late 2000s.(04:19) Shinji shared valuable lessons learned from her undergraduate co-op experience with statistical analysis at Sun Microsystems, software engineering at Barclays Capital, and growth marketing at Facebook.(08:52) Shinji shared lessons learned from being a Management Consultant at Deloitte.(14:01) Shinji revisited her decision to quit the job at Deloitte and create a social puzzle game called Shufflepix.(17:42) Shinji went over her time working as a Product Manager at the mobile ad exchange network YieldMo.(22:25) Shinji discussed the problem of stream processing at YieldMo, which sparked the creation of Concord.(26:17) Shinji unpacked the pain points with existing stream processing frameworks and the competitive advantage of using Concord.(33:19) Shinji recalled her time at Akamai — initially as a data engineer in the Platform Engineering unit and later as a product manager for the IoT Edge Connect platform.(37:26) Shinji explained why sharing context knowledge around data remains a largely unsolved problem.(42:07) Shinji unpacked the three capabilities of an ideal data discovery platform: (1) exposing up-to-date operational metadata along with the documentation, (2) tracking the provenance of data back to its source, and (3) guiding data usage.(46:59) Shinji unpacked the benefits of plugging BI tools into data discovery platforms and collecting metadata, which facilitates better visibility and understanding.(52:36) Shinji discussed the role of a data discovery platform within the modern data stack.(53:59) Shinji shared the hurdles that her team has to go through while finding early adopters of Select Star.(55:48) Shinji shared valuable hiring lessons learned at Select Star.(01:00:00) Shinji shared fundraising advice for founders currently seeking the right investors for their startups.(01:04:41) Closing segment.Shinji’s Contact InfoLinkedInTwitterMediumSelect Star’s ResourcesWebsiteBlogLinkedIn | Twitter | MediumMentioned ContentArticles“The Next Evolution of Data Catalogs: Data Discovery Platforms” (Feb 2021)“Data Discovery for Business Intelligence” (May 2021)PeopleMartin Kleppmann (Author of Designing Data-Intensive Applications)Emily Riederer (Senior Analytics Manager at Capital One)Anya Prosvetova (Tableau DataDev Ambassador)Book“Managing Oneself” (by Peter Drucker)Notes
My conversation with Shinji was recorded back in July 2021. Since then, many things have happened at Select Star:
General Availability launch on Product Hunt: https://www.producthunt.com/posts/selectstarSnowflake partnership on data governance: https://blog.selectstar.com/selectstar-and-snowflake-partner-to-take-data-governance-to-a-new-level-a9d274e1d4c6Case studies with Pitney Bowes and HandshakeAbout the showDatacast 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. Get in touch with feedback or guest suggestions by emailing [email protected].
Subscribe by searching for Datacast wherever you get podcasts or click one of the links below:
Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.
About the show
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:
Listen on SpotifyListen on Apple PodcastsListen on Google PodcastsIf you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.