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

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.

ABOUT DATA COUNCIL: Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers.

Make sure to subscribe to our channel for the most up-to-date talks from technical professionals on data related topics including data infrastructure, data engineering, ML systems, analytics and AI from top startups and tech companies.

FOLLOW DATA COUNCIL: Twitter: https://twitter.com/DataCouncilAI LinkedIn: https://www.linkedin.com/company/datacouncil-ai/

Data teams aren't only working in Excel and Tableau anymore. We're working in GitHub, VSCode, BigQuery, and our command line. We have the modern data pipeline and we're developing a lot more like engineers...but our development workflows are anything but modern. Why don't we get developer previews? Or the ability to test our changes to anything downstream of dbt? Why do our tools not talk to each other? We believe that analytics engineers deserve better and we want to show you what "better data development" could look like in the modern data pipeline (we promise, it's really nice).

Check the slides here: https://docs.google.com/presentation/d/1NtAOknFDmJiIQD6cSTbhmfZ-6ZFhKKH3GKcEZ3AL5eg/edit?usp=sharing

Coalesce 2023 is coming! Register for free at https://coalesce.getdbt.com/.