Sign up to save your podcasts
Or
Share Episode 72: Folding Data with Gleb Mezhanskiy
Share to email
Share to Facebook
Share to X
Share to email
Share to Facebook
Share to X
Or
Episode 72: Folding Data with Gleb Mezhanskiy
Timestamps
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit datacast.substack.com/subscribe
- (01:42) Gleb shared briefly about his upbringing and studying Economics in university in Russia.
- (04:15) Gleb discussed his move to the US to pursue a Master of Information Systems Management at Carnegie Mellon University.
- (07:07) Gleb went over his summer internship as a Business Analyst at Autodesk.
- (08:40) Gleb shared the details of his project architecting data model/ETL pipelines as a PM at Autodesk.
- (11:34) Gleb unpacked the evolution of his career at Lyft — from an individual data analyst to a PM on data tooling and a high-impact project that he worked on.
- (16:54) Gleb shared valuable lessons from the experience of leading multiple cross-functional teams of engineers and growing the data organization significantly.
- (19:48) Gleb mentioned his time as a Product Manager at Phantom Auto, leading the development of a teleoperation product for autonomous vehicles over cellular networks.
- (25:28) Gleb emphasized the critical factors to consider when choosing a working environment: trusted managers/colleagues, maturity of tools/processes, and the function of data teams within the organization.
- (29:10) Gleb shared the story behind the founding of Datafold, whose mission is to help companies effectively leverage their data assets while making Data Engineering & Analytics a creative and enjoyable experience.
- (33:04) Gleb dissected the pain points with regression testing and the benefits of using Data Diff (Datafold’s first product) for data engineers.
- (36:54) Gleb unpacked the data monitoring feature within Datafold’s data observability platform.
- (39:45) Gleb discussed how to choose data warehousing solutions for your use cases (and made the distinction between data warehouse and data lake).
- (47:03) Gleb gave insights on the need for BI and data observability/quality management tools within the modern analytics stack.
- (50:40) Gleb emphasized the importance of tooling integration for Datafold’s roadmap.
- (52:07) Gleb has been hosting Data Quality meetups to discuss the under-explored area of data quality.
- (54:02) Gleb shared his learnings from going through the YC incubator in summer 2020.
- (55:45) Gleb discussed the hurdles he had to jump through to find early customers of Datafold.
- (57:47) Gleb emphasized valuable lessons he has learned to attract the right people who are excited about Datafold’s mission.
- (59:17) Gleb shared his advice for founders who are in the process of finding the right investors for their companies.
- (01:02:11) Closing segment.
- Datafold (Twitter and LinkedIn)
- Data Quality Meetups
- Harvard’s CS50: Introduction to Computer Science
- Modern Analytics Stack (June 2020)
- Choosing Data Warehouse for Analytics (June 2020)
- 3 Ways To Be Wrong About Open-Source Data Warehousing Software (June 2020)
- Buy Not Build (Aug 2020)
- Datafold Raises a $2.1M Seed Round Led by NEA (Nov 2020)
- Datafold + dbt: The Perfect Stack for Reliable Data Pipelines (Feb 2021)
- Maxime Beauchemin (Founder and CEO at Preset, creator of Apache Superset and Apache Airflow)
- Tobias Macey (Host of the Data Engineering Podcast)
- “How To Measure Anything” (by Douglas Hubbard)
- “Lean Analytics” (by Benjamin Yoskovitz and Alistair Croll)
My conversation with Gleb was recorded back in March 2021. Since the podcast was recorded, a lot has happened at Datafold! I’d recommend:
- Reading Gleb’s open-source edition of the modern data stack.
- Listening to Gleb’s appearance on the Data Engineering podcast.
- Watching the lightning talks and panel discussions from recent Data Quality meetups number 4 and number 5.
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. 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 Spotify
- Listen on Apple Podcasts
- Listen on Google Podcasts
If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit datacast.substack.com/subscribe
View all episodes
By James LeTimestamps
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit datacast.substack.com/subscribe
- (01:42) Gleb shared briefly about his upbringing and studying Economics in university in Russia.
- (04:15) Gleb discussed his move to the US to pursue a Master of Information Systems Management at Carnegie Mellon University.
- (07:07) Gleb went over his summer internship as a Business Analyst at Autodesk.
- (08:40) Gleb shared the details of his project architecting data model/ETL pipelines as a PM at Autodesk.
- (11:34) Gleb unpacked the evolution of his career at Lyft — from an individual data analyst to a PM on data tooling and a high-impact project that he worked on.
- (16:54) Gleb shared valuable lessons from the experience of leading multiple cross-functional teams of engineers and growing the data organization significantly.
- (19:48) Gleb mentioned his time as a Product Manager at Phantom Auto, leading the development of a teleoperation product for autonomous vehicles over cellular networks.
- (25:28) Gleb emphasized the critical factors to consider when choosing a working environment: trusted managers/colleagues, maturity of tools/processes, and the function of data teams within the organization.
- (29:10) Gleb shared the story behind the founding of Datafold, whose mission is to help companies effectively leverage their data assets while making Data Engineering & Analytics a creative and enjoyable experience.
- (33:04) Gleb dissected the pain points with regression testing and the benefits of using Data Diff (Datafold’s first product) for data engineers.
- (36:54) Gleb unpacked the data monitoring feature within Datafold’s data observability platform.
- (39:45) Gleb discussed how to choose data warehousing solutions for your use cases (and made the distinction between data warehouse and data lake).
- (47:03) Gleb gave insights on the need for BI and data observability/quality management tools within the modern analytics stack.
- (50:40) Gleb emphasized the importance of tooling integration for Datafold’s roadmap.
- (52:07) Gleb has been hosting Data Quality meetups to discuss the under-explored area of data quality.
- (54:02) Gleb shared his learnings from going through the YC incubator in summer 2020.
- (55:45) Gleb discussed the hurdles he had to jump through to find early customers of Datafold.
- (57:47) Gleb emphasized valuable lessons he has learned to attract the right people who are excited about Datafold’s mission.
- (59:17) Gleb shared his advice for founders who are in the process of finding the right investors for their companies.
- (01:02:11) Closing segment.
- Datafold (Twitter and LinkedIn)
- Data Quality Meetups
- Harvard’s CS50: Introduction to Computer Science
- Modern Analytics Stack (June 2020)
- Choosing Data Warehouse for Analytics (June 2020)
- 3 Ways To Be Wrong About Open-Source Data Warehousing Software (June 2020)
- Buy Not Build (Aug 2020)
- Datafold Raises a $2.1M Seed Round Led by NEA (Nov 2020)
- Datafold + dbt: The Perfect Stack for Reliable Data Pipelines (Feb 2021)
- Maxime Beauchemin (Founder and CEO at Preset, creator of Apache Superset and Apache Airflow)
- Tobias Macey (Host of the Data Engineering Podcast)
- “How To Measure Anything” (by Douglas Hubbard)
- “Lean Analytics” (by Benjamin Yoskovitz and Alistair Croll)
My conversation with Gleb was recorded back in March 2021. Since the podcast was recorded, a lot has happened at Datafold! I’d recommend:
- Reading Gleb’s open-source edition of the modern data stack.
- Listening to Gleb’s appearance on the Data Engineering podcast.
- Watching the lightning talks and panel discussions from recent Data Quality meetups number 4 and number 5.
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. 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 Spotify
- Listen on Apple Podcasts
- Listen on Google Podcasts
If you’re new, see the podcast homepage for the most recent episodes to listen to, or browse the full guest list.
This is a public episode. If you'd like to discuss this with other subscribers or get access to bonus episodes, visit datacast.substack.com/subscribe