David Jayatillake joins me to chat about semantic layers, assessing value in data work, AI, and much more.
David's LinkedIn: https://www.linkedin.com/in/david-jayatillake/
talk-data.com
Speaker
David Jayatillake
5
talks
VP of AI - Cube
Metaplane
David Jayatillake is currently the VP of AI at Cube. Before Cube, he founded Delphi Labs, an AI company that provides a natural language interface to data while ensuring safe answers and guardrails. David is a data Leader with experience in Credit, Payments, Pricing, Revenue Management, e-commerce and retail. He is commercially astute, with strong C-level and global stakeholder management and a collaborator with good presentation skills and an ambition to improve business performance.
Bio from: dbt Coalesce 2022
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Most organizations are using GenAI in hopes of gaining easy access to information needed by their users to enable greater productivity. At the same time, it's also well-documented that LLMs can deliver inaccurate information. To be of value, users need to be able to trust that the answers presented to them are correct.
This is a key issue at the center of AI adoption and its applications in the real world. For example, many organizations are beginning to develop, test, and implement chatbots for internal and external use to provide answers to questions by using natural language. When those chatbots do not produce the right answers, all the time and effort put into creating them ends up wasted.
Join David Jayatillake, Cube's VP of AI, for an in-depth discussion on the current state of GenAI and the rise of the semantic layer.
In this talk, you will learn about:
The current state of GenAI
The rise of the semantic layer in modern data stack with AI
The significant differences between an AI chatbot with and without a semantic layer
As analytics engineers and data people, we know the value we create in our own blood, sweat, and dbt models. But how is this value actually realized in practice? In this talk, David Jayatillake (Metaplane) draws on his experiences to discuss the processes, ways of thinking, tooling, and governance needed to realize the benefits from analytics engineering work in the greater organization.
Check the slides here: https://docs.google.com/presentation/d/1VmmqNQsrv1t0uuV81O6PJQ1XASyLRGxvAdB8eWIG9TQ/edit?usp=sharing
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A debate has erupted on data Twitter and data Substack - should the modern data stack remain unbundled, or should it consolidate? In this conversation, Benn Stancil (Mode), David Jayatillake (Avora) and our host Tristan Handy try to make some sense of this debate, and play with various future scenarios for the modern data stack. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.
David is Sr. Director of Data at Lyst, and as leader of their analytics + data science teams he has followed the evolution of data roles closely over the past decade. David spends a lot of time thinking about career progression + data team structure, and in this conversation with Tristan + Julia they dive into the classic individual contributor vs manager conundrum, migrating between warehouses, and reactive vs proactive data workflows. For full show notes and to read 6+ years of back issues of the podcast's companion newsletter, head to https://roundup.getdbt.com. The Analytics Engineering Podcast is sponsored by dbt Labs.