Cassandra (Cassie) Shum

RelationalAI
VP of Field Engineering

Biography

Cassie Shum is the VP of Field Engineering for RelationalAI. She leads a large group of highly specialized data scientists, knowledge graph experts, and software architects and engineers implementing the RAI product in enterprise organizations. Her previous years include a background as a software engineer and architect; she has spent the last 18+ years focusing on building highly scalable and resilient architectures, including event-driven systems and microservices on cloud-based technologies. Cassie has been focused on a wide range of technologies with an emphasis on data, cloud, mobile, and software delivery excellence. She was a member of the ThoughtWorks Technology Advisory Board and contributed to the creation of the ThoughtWorks Technology Radar. Cassie had also been involved in growing not only organizations in the delivery practices and technical strategy but also the next generation of technologists. Some of her passions include advocating for women in technology and public speaking. She is also involved in promoting more female speakers in technology.

Talks and Events

Accelerate Data Products in Financial Services with a Semantic Layer

In financial services, a common language and data model are essential to not only meet regulatory needs but also to stay competitive by creating more products more quickly and monetizing on massive amounts of accumulated, heterogeneous data. In fact, we see an increasing number of semantic layer and modeling tools such as Legend, Morphir, and others coming into the open source realm and gaining adoption amongst other institutions to try to address this. Historically, however, there are challenges with integrating and executing these semantic layers within an existing data infrastructure ecosystem at scale. This often results in obstacles to adoption and difficulties in transitioning efforts to production.

In this talk, we will provide a specific example of how we use relational semantic layers to solve this challenge through a financial services use case. You’ll learn about semantic layers in financial services and how a relational semantic layer fits in a modern data stack. You’ll also get a technical review of an applied financial services use case involving PURE/Legend, and find out how the business benefits from having a generic model of representation and execution that spans all data sources and types (e.g., semistructured, graph, tabular, etc.). The talk will end with forward-looking thoughts on the industry and a chance for you to ask questions of some of the experts implementing these solutions.

Track: Semantic Layer

Session Topics:

  • Semantic Layer
  • Business Use Cases
  • Financial Services