The Analytics Everywhere Podcast

Welcome to this episode of the Analytics Everywhere podcast! In episode #6, Max chats with Byron Allen, the ML Practice Lead at Contino.  In this episode, we chat about a variety of topics around the challenges of operationalizing data:  

- organizational difficulties around data (data mesh vs centralized data warehouse / governance) 

- what a semantic layer really is 

- thin vs thick semantic layers 

- entity / dataset centric modelling 

- the idea of a unified semantic layer for ML and BI 

- batch vs real-time ML use cases 

- experimentation frameworks 

- and much much more!  

We hope you enjoy this episode!

Links: 

Byron Allen: https://www.linkedin.com/in/byronaallen/

Byron Allen's conversation about entity centric modeling: https://youtu.be/9YcLBSqZNzE?t=2977

Drew Banin's talk at apply(): https://www.tecton.ai/apply/session-video-archive/the-dbt-semantic-layer/ 

Preset: https://preset.io/product

Subscribe to the podcast here: https://anchor.fm/analytics-everywhere

Welcome to this live episode of the Analytics Everywhere podcast! In episode #4, Max chats with Michel Tricot, the co-founder and CEO of Airbyte.   In this episode, we talk about the challenges of data integration, the importance of establishing protocols for data connectors, how traditional REST API's fall short when it comes to data exhaust, the original idea for Airbyte that got them into YCombinator, and much much more.  

We hope you enjoy this episode!

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Links: 

Michel Tricot: https://www.linkedin.com/in/micheltricot/ 

Airbyte: https://airbyte.com/ 

Preset: https://preset.io/product 

Subscribe to the podcast here: https://anchor.fm/analytics-everywhere

Welcome to this live episode of the Analytics Everywhere podcast! In episode #4, Max chats with dbt co-founder Drew Banin about the the history of dbt, Airflow vs the dbt view of data engineering, the dbt semantic layer, and more.  We hope you enjoy this episode! 

Links:  

Drew Banin: https://www.linkedin.com/in/drewbanin

Preset: https://preset.io/product/

dbt: http://dbt.com/

Subscribe to the Analytics Everywhere Podcast here: https://anchor.fm/analytics-everywhere

Welcome to this live episode of the Analytics Everywhere podcast! In episode #3, Max chats with Zach Wilson from Airbnb about building data products. They talk about some of the data engineering patterns they witnessed at both small and large tech companies, data applications, and more. We end this episode with some great Q&A from the audience.

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Watch the video recording here: https://preset.io/events/the-analytics-everywhere-podcast-live-episode-with-zach-wilson/

Zach Wilson: https://www.linkedin.com/in/eczachly/

Max Beauchemin: https://www.linkedin.com/in/maximebeauchemin/

Srini Kadamati: https://www.linkedin.com/in/srinivasakadamati/

In this episode, we sit down with Pavel Tiunov, the CTO of Cube. Cube is a headless BI platform that seeks to be the serving layer for interactive analytics applications. Cube’s story is pretty interesting, because they started out as a different company with a different name before pivoting completely.  This conversation is all about headless BI, a recent trend within the modern data stack that revolves around pushing charts, dashboards, and analytics experiences out of the traditional container of internal BI.

Welcome to the Analytics Everywhere podcast, presented by Preset (the experts of Apache Superset). This podcast is dedicated to understanding the perspectives of the builders of next generation data tools and the impact those tools seek to have on the end user analytics experience. 

In episode 1, Max and Srini from Preset speak with Chris Riccomini on the data mesh. 

Who:

Chris Riccomini created Apache Samza, a streaming framework on top of Apache Kafka, while at LinkedIn and then went on to help manage data engineering at WePay. Max Beauchemin is the original creator of Apache Airflow and Apache Superset and is Preset's founder and CEO. Srini Kadamati is a Senior Developer Advocate at Preset.

Episode Overview:

If you're new to the data mesh, don't worry! We start by getting a great definition of the data mesh by Chris. The episode then goes on to discuss the challenges of large scale data infrastructure that both Chris and Max have encountered at organizations like Airbnb, Lyft, Facebook, and LinkedIn. We also discuss Snowflake's data clean room, building data products more generally, data tools that Max and Chris wish existed, and even Matt Damon!

We hope you enjoy this first episode! If you have thoughts or feedback, please reach out to me at srini@preset.io