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In 2021, semantic layers took the data world by storm—it felt like they came out of nowhere, then everyone was talking about them. Since then, companies have been built (and some have failed) on the promise of the semantic layer, blog posts have debated their rise and fall, and data teams are still left wondering: was it all just hype, or are semantic layers truly the next big thing in data? In this talk, I'll explore the evolution of the semantic layer and answer the burning question: Is it here to stay, or is it just a passing trend?

Speaker: Katie Hindson Head of Product and Data Lightdash

Read the blog to learn about the latest dbt Cloud features announced at Coalesce, designed to help organizations embrace analytics best practices at scale https://www.getdbt.com/blog/coalesce-2024-product-announcements

London Analytics Meetup #7 - Big Data London 2024 week

At Zego’s office in the City of London near Liverpool Street Station!

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We’ll have some food and drink courtesy of Paradime.

Talks:

Katie Hindson - VP of Product @ Lightdash - Semantic Layers: The next data revolution or just overrated hype?

Francesco Puppini - co-author of the Unified Star Schema

Germán Lopez-Campos - Lead Data Engineer @ Zego - Cost and efficiency enhancements at Zego

ABOUT THE TALK: Building data tools requires us to not only think about the data team, but also about the people that the data team is serving: business users, or "non-data team people".

This talk will go over how it's super important to consider these two personas when building data tools, but it can also be a bit complicated. We will talk through a few principles we can use to build data products that are great for everyone (not just the data team!)

ABOUT THE SPEAKER: As a product manager with a background in data science, Katie Hindson loves building data products. Currently, she's working at Lightdash, an open-source BI tool that instantly turns your dbt project into a full-stack BI platform. Katie is really interested in the interaction between data teams, their tools, and the rest of the company - because the best data teams are the ones that can help everyone at the company make better decisions, faster.

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