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Episode 174:

Does Your Data Stack Need a Semantic Layer? Featuring Artyom Keydunov of Cube Dev

January 24, 2024

This week on The Data Stack Show, Eric and Kostas chat with Artyom Keydunov, Co-Founder and CEO, Cube Dev. During the episode, the group discusses the evolution of semantic layers, their importance in data management, and Cube’s growth and adaptation to industry needs. Artyom highlights the challenges in building a semantic layer and the solutions Cube has developed, including their own SQL engine. He also discusses the potential of integrating semantic layers with natural language processing technologies for improved accuracy and much more.

Notes:

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.

About the Podcast

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.

To keep up to date with our future episodes, subscribe to our podcast on Apple, Spotify, Google, or the player of your choice.

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