Self-serve analytics promises speed. But without clear guidance, it often leads to hidden obstacles like cluttered dashboards, runaway costs, and a loss of trust in the data. Add AI to the mix, and those faults become fractures. In this session, we'll unpack why self-serve efforts stall, with lessons from real-world teams at Shopify and Tableau. We’ll also explore how BetterHelp uses dbt alongside Euno’s lineage and usage insights to declutter, cut compute costs, and determine which data assets and reports teams (and AI agents) can trust.

Practicing analytics well takes more than just tools and tech. It requires data modeling practices that unify and empower all teams within analytics, from engineers to analysts. This is especially true as AI becomes a part of analytics. Without a governed data model that provides consistent data interpretation, AI tools are left to guess. Join panelists Joe Reis, Sarah Levy, Harry Gollop, Rob Hulme, Shachar Meir, and Guy Fighel, as they share battle-tested advice on overcoming conflicting definitions and accurately mapping business intent to data, reports and dashboards at scale. This panel is for data & analytics engineers seeking a clear framework to capture business logic across layers, and for data leaders focused on building a reliable foundation for Gen AI.

Managing metrics across teams can feel like everyone’s speaking a different language, which often leads to loss of trust in numbers. Based on a real-world use case, we’ll show you how to establish a governed source of truth for metrics that works at scale and builds a solid foundation for AI integration. You’ll explore how Bolt.eu’s data team governs consistent metrics for different data users and leverages Euno’s automations to navigate the overlap between Looker and dbt. We’ll cover best practices for deciding where your metrics belong and how to optimize engineering and maintenance workflows across Databricks, dbt and Looker. For curious analytics engineers, we’ll dive into thinking in dimensions & measures vs. tables & columns and determining when pre-aggregations make sense. The goal is to help you contribute to a self-serve experience with consistent metric definitions, so business teams and AI agents can access the right data at the right time without endless back-and-forth.

Sarah Levy (CEO of Euno) joins me to chat about modern data governance for analytics.

Euno - https://euno.ai/

We’re improving DataFramed, and we need your help! We want to hear what you have to say about the show, and how we can make it more enjoyable for you—find out more here. Imagine spending millions on data tools only to find you can’t trust the answers they provide. What if different teams define key metrics in different ways? Without a clear, unified approach, chaos reigns, and confidence erodes. What role do data governance and semantic layers play in helping you trust the AI tools you build and the insights you get from your data? Sarah Levy is a seasoned executive with extensive experience in data science, artificial intelligence, and technology leadership. Currently serving as Co-Founder and CEO of Euno since January 2023, Sarah has previously held significant positions, including VP of Data Science and Data Analytics for Real Estate at Pagaya and CTO at Sight Diagnostics, where innovative advancements in blood testing were achieved. With a strong foundation in research and development from roles at Sight Diagnostics and Natural Intelligence, as well as a robust background in cyber security gained from tenure at the IDF, Sarah has consistently driven impactful decision-making and technological advancements throughout their career. Academic credentials include a Master's degree in Condensed Matter Physics from the Weizmann Institute of Science and a Bachelor's degree in Mathematics and Physics from The Hebrew University of Jerusalem. In the episode, Richie and Sarah explore the challenges of data governance, the role of semantic layers in ensuring data trust, the emergence of analytics engineers, the integration of AI in data processes, and much more. Links Mentioned in the Show: EunoConnect with SarahCourse: Responsible AI Data ManagementRelated Episode: How Data Leaders Can Make Data Governance a Priority with Saurabh Gupta, Chief Strategy & Revenue Officer at The Modern Data CompanyRewatch sessions from RADAR: Forward Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

Adopting dbt marks a significant leap towards governed data transformations. But with every game-changer, big questions arise: Where do data transformations end? Should they touch the BI layer? What roles do data engineers, analytics engineers, and business analysts play in data modeling? And, is centralizing metrics truly beneficial? Spoiler: It's about finding the balance between freedom and governance.

Our expert panelists will share best practices for scaling dbt to handle transformations and metrics without stifling analyst freedom or causing team burnout. You'll learn how to build a robust metrics layer in dbt and manage business logic as your data operation grows, all by establishing a solid foundation with dbt.

Speakers: Mark Nelson, Silja Mardla, Patrick Vinton, Sarah Levy

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

In an era where data drives decision-making and innovation, data engineering stands at the forefront of technological advancement. 

This panel brings together leading experts; Chad Sanderson, Joe Reiss, Sarah Levy and Pushkar Garg to explore the critical challenges and opportunities shaping the field today.