DATE: June 12, 2024

TIME: 8:00 AM – 12:45 PM Pacific / 11:00 AM – 3:45 PM Eastern

PRICE: Free to all attendees

Welcome to DATAVERSITY Demo Day, an online exhibit hall. We’ve had many requests from our data-driven community for a vendor-driven online event that gives you an opportunity to learn more about the available tools and services directly from the vendors that could contribute to your Data Architecture program’s success.

Register to attend one or all of the sessions, or in order to receive the follow-up email with links to the slides and recordings.

Session 1: How to Automate AI-Powered Data Mesh

Using artificial intelligence (AI) to assist in automating the creation of data products in a data mesh has the potential to revolutionize the way you manage your data. By automating the tasks involved in managing a data mesh, AI can free up data professionals to focus on more strategic tasks, such as developing new machine learning and generative AI capabilities. AI-based data management automation allows for improved data quality, reduction in engineering costs, increased data accessibility, and faster time-to-market for data products. 

Session 2: Coding with NoSQL – Vector Search and RAG 

Do you like the familiarity of SQL, but need the speed and flexibility of JSON data to build adaptive applications? Matthew Groves and Tyler Mitchell will show you how to get the best of both worlds from a single NoSQL database that takes advantage of SQL++, the de facto standard for applying SQL to JSON data. We’ll also demo some of Couchbase’s latest features for building with AI and using AI for building: Vector Search and RAG. 

Session 3: Next-Gen Data Integration – Exploring Denodo’s Dynamic Data Architectures for Modern Enterprises

Discover how Denodo’s modern approach to data integration and abstraction enables organizations to break down data silos, accelerate data access, and drive business agility. In this session, we will explore the key components of Denodo’s data architecture, its benefits, and real-world use cases illustrating its effectiveness in driving data-driven decision-making.