The field of data analysis and visualization is experiencing significant advancements with the integration of Large Language Models (LLMs). Researchers are exploring the potential of LLMs to improve qualitative data analysis, automate deductive coding of dialogue data, and generate design rationale for software architecture decisions. These innovations aim to reduce manual effort, enhance accuracy, and provide valuable insights into complex data. Notably, LLMs are being leveraged to support systematic software design, facilitate contextual understanding, and recover design rationale. The community is also reflecting on the challenges and trends in visual analytics, highlighting the need for effective human-data interaction in the age of AI. Noteworthy papers include: Using LLMs in Generating Design Rationale for Software Architecture Decisions, which evaluated the performance of LLMs in generating design rationale with promising results. Data Therapist: Eliciting Domain Knowledge from Subject Matter Experts Using Large Language Models, which presented a web-based tool that combines iterative Q&A with interactive annotation to externalize implicit knowledge from domain experts.