Thursday March 13, 2025 @ 4-5PM PST Register Here Session Synopsis AI Governance involves managing the trade-offs between innovation and risk management for artificial intelligence. This session will cover the following topics based on Sunil Soares’ books on AI Governance: Sunil Soares, Private Equity Exit/IAPP AIGP Speaker Bio Sunil Soares is the Founder and CEO…
Category: Chapter Meetings
February 2025: Data Governance by Design
We have shifted our focus from governing data when an initiative is complete, to beginning data governance during the design phase of the software development lifecycle. We walk with our development teams to ensure that governance is baked into the plan, not an afterthought. We determine the level of governance that is needed for new data products during design. This ensures that the development teams are not surprised by our governance requirements, reducing remediation, and improving the quality of the data products from their inception.
January 2025: Have your Data Quality Cake and Eat It Too (with AI)
In this information-packed session, Data Quality Practitioner, Dan Myers (DQMatters) will provide an update on the state of data quality in the industry based on his 9-year running survey published in November 2024. Then he’ll explain how an industry standard set of dimensions of data quality (the cake) enables consistent communication between data professionals. Dan will demonstrate how to leverage two free AI tools that can help junior team members improve data quality (eat the cake). It isn’t a panacea, but you’re at a disadvantage to ignore these tools.
September 2024: Semantic Layer Architecture
This session will present case studies that take a deep dive in the technical architecture of a Semantic Layer, exploring the components that enable semantic capabilities, such as metadata management, data catalogs, ontology/knowledge graphs and AI infrastructure. The presentation will emphasize how these components interconnect organizational knowledge and data assets, enhancing systems like recommendation engines and semantic search and explore the top three common approaches we are seeing at play in order to weave this data and knowledge layer into the fabric of enterprise architecture, highlighting the applications and organizational considerations for each.
October 2023: Benefits of Top-down Data Modeling
In this presentation we will explore the benefits of top-down modeling approaches and emphasize the value of top-down modeling in data warehousing and highlight the importance of ontologies. We will discuss “why” top-down models should be considered, “how” to develop these models and apply it to your data warehousing initiatives.