In this bonus episode, Eric and Kostas preview their upcoming discussion with a panel of experts as Wes McKinney (Co-Founder, Voltron), Pedro Pedreira Software Engineer, Meta), Chris Riccomini (Seed Investor, various startups), and Ryan Blue (Co-Founder and CEO, Tabular) join the show.

Highlights from this week’s conversation include:Artyom’s background in the data space (0:32)The growth and changes at Cube (5:58)Pain points of managing metrics definitions across different tools (9:39)Trade-offs between coupled and decoupled semantic layers (12:12)Making a case for implementing a semantic layer (14:17)The evolution of semantic layers (23:28)Challenges in designing a decoupled semantic layer (24:16)Different approaches to solving the interface problem (26:58)Implementing a SQL engine in Cube (35:58)Overhead and debugging in semantic layers (39:08)The semantic layer and its importance (46:26)The need for semantics in data products (47:34)What’s the future of semantic layers and user experience? (51:49)Final thoughts and takeaways (57:34)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

In this bonus episode, Eric and Kostas preview their upcoming conversation with Artyom Keydunov of Cube Dev.

Highlights from this week’s conversation include:No Code Analytics (1:22)Analytics as a Team Sport (2:31)The workflow of someone without Alteryx (11:27)Alteryx's ability to handle diverse data sources (14:32)The balance between ease of use and complexity (23:06)Enabling casual end users with a no code interface (24:19)Taking analytics to the data (31:47)The boundaries between data engineers and end users (33:44)The importance of collaboration in analytics (34:12)The potential of every employee being a data worker (35:28)The human nature of the product and users in large enterprises (00:45:38)Final thoughts and takeaways (46:21)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.

In this bonus episode, Eric and Kostas preview their upcoming conversation with Jay Henderson of Alteryx.

Matt Butcher, Co-founder of Fermyon Technologies and WebAssembly expert, discusses his background, the potential of WebAssembly for cloud computing, the benefits of WebAssembly, and the challenges and progress in this field. Topics include enhanced security models, Google's early containers, scaling and anticipating requests, comparison of virtual machines, containers, and micro VMs, fast startup times in WebAssembly, metaphysics and software development, effective communication in code development, and requirements of different teams and jobs.

In this bonus episode, Eric and Kostas preview their upcoming conversation with Matt Butcher of Fermyon Technologies.

Guest Sandy Ryza, an expert in machine learning pipelines, discusses the role of orchestrators in the lifecycle of data, changes in data ops and MLOps, data cleaning, and the overview of Dagster. They also explore the difference between data assets and tasks in data pipelines, defining lineage and data assets in Dagster, and the benefits of a unified orchestration framework. Additionally, they touch on orchestration in the development phase and the emergence of the analytics engineer role.

Sandy Ryza from Dagster Labs discusses the role of an orchestrator in Data Ops and ML Operations. They also emphasize the need for diverse solutions in the ML operations space.

Highlights from this week’s conversation include:The evolution of the data scientist role (1:03)Common problems in different companies (2:05)Measuring and curating content on Reddit (4:29)The challenges of working with unstructured content at Reddit and Twitter (11:03)Lessons learned from Reddit and applying them at Twitter (13:17)Data challenges and customer behavior analysis at GlossGenius (20:16)How the data scientist's role has changed over time (00:25:10)The essence of the data scientist/engineer role (29:00)Dynamics and overlaps between different data roles (32:09)The perfect data team for Twitter (34:19)Building a data team at a startup like GlossGenius (36:36)The right time to bring in a dedicated data person in a startup (38:52)The analytics engineer role (46:25)Challenges in implementing telemetry (50:31)Final thoughts and takeaways (52:24)The Data Stack Show is a weekly podcast powered by RudderStack, the CDP for developers. Each week we’ll talk to data engineers, analysts, and data scientists about their experience around building and maintaining data infrastructure, delivering data and data products, and driving better outcomes across their businesses with data.RudderStack helps businesses make the most out of their customer data while ensuring data privacy and security. To learn more about RudderStack visit rudderstack.com.