Every organization faces unique challenges in becoming data-driven. This practical half-day session guides attendees through creating a modern data architecture that aligns with your business strategy to deliver ongoing and scalable value. Through our proven four-step methodology, attendees learn to translate business goals into architectural decisions and evaluate emerging technologies from cloud-native platforms, data lakehouses, and data fabrics to build a prioritized road map. Data leaders gain frameworks to assess which modern data stack components best serve their organization's specific needs and capabilities. Most importantly, attendees leave with actionable insights that will motivate them to transform their data infrastructure and drive business outcomes.

Semantic layers stand out as a key approach to solving business problems for organizations grappling with the complexities of managing and understanding the meaning of their data. A semantic layer, also called context layer, is a business representation of data that allows organizations to quickly map various data definitions from multiple data sources to familiar business terms, offering a consistent and consolidated view of data. Join our workshop to gain insights into the foundations of semantic/context layers, their implementation, and the business value they provide by enhancing the utility of your data. The workshop promises an interactive experience, offering participants the opportunity to both understand the nuances of semantic/context layers and actively engage in constructing one.

Data teams are deluged with user requests for datasets, metrics, or reports. They need help finding, accessing, validating, or fixing data. For many data leaders, the solution is simple: Empower users to service their own data and analytics needs. But what is easy to say is challenging to do. This workshop provides practical, time-tested approaches to democratizing data and creating an insights-driven culture. It shows how data teams can eliminate data bottlenecks by transforming themselves from order takers to strategic business partners who proactively anticipate business needs. However, the path to self-service nirvana is not for the faint-hearted: It requires developing a deep knowledge of business user needs and then overhauling the team's operating model, data architecture, data governance, data delivery, and support networks to meet those needs.

While fine-tuned large language models (LLMs) excel at simple coding tasks, they often struggle with complex code, specialized libraries, and detailed applications. This workshop addresses the challenge of LLM hallucinations by introducing a method of breaking down training data into smaller, descriptive components that build sequentially into complex code. Learn how this structured approach enables even smaller LLMs running on consumer-grade GPUs to perform significantly better. Jacob shares real-world experiences in fine-tuning code generators for modern AI libraries such as LangChain and Vertex AI. With enhanced dataset representation, models produce more accurate, library-aligned code. He covers practical strategies for improving LLM performance in specialized code generation tasks. Attend this workshop to learn how to improve LLM code generation through innovative dataset representation strategies.