In this episode of the Data Science Salon Podcast, we sit down with Carlos Aguilar, Head of Product at Hex and former founder of Hashboard, to discuss a topic critical for every data team: how to properly evaluate AI analytics tools.

Carlos shares why traditional checklist-based evaluations fail for conversational AI and generative analytics tools, and how focusing on context, workflow, and real user testing can dramatically improve the chances of success. Drawing on his experience leading the Data Insights team at Flatiron Health, he provides practical guidance for both end-users and data teams.

Key Highlights:

• End-User vs Data Team Evaluation: Why both perspectives are crucial for measuring AI effectiveness.
• Context Management: How setting up reference questions ensures accurate and relevant answers.
• Workflow & Observability: Why monitoring and iterating on AI outputs is essential for real-world success.
• Lessons from the Field: Examples of tools that look good in demos but fail in production—and how to avoid those pitfalls.

🎧 Tune in to Episode 60 to learn how to evaluate AI analytics tools the right way and ensure your data teams deploy solutions that actually work in practice.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

Together, Leon and Oscar share how applied EDA practices remain the backbone of trustworthy analytics pipelines in both academic and industry settings. Their discussion highlights the challenges and lessons learned from building the EDA Toolkit, and why reproducible workflows are more important than ever in the age of AI and ML.

Key Highlights:

• Reproducible EDA: How to standardize exploratory data analysis workflows for consistent and trustworthy insights.
• Open-Source Innovation: The design and impact of the EDA Toolkit, bridging research, healthcare, and education.
• Best Practices for Analytics: Lessons learned from creating tools that make EDA more intuitive and scalable across projects.
• The Future of Data Science Workflows: Why reproducibility and standardization matter in modern AI/ML pipelines.

🎧 Tune in to Episode 59 to hear Leon Shpaner and Oscar Gil’s insights on building reproducible, reliable, and effective data science workflows, and how open-source tools can transform analytics practices across domains.

Be sure to mark your calendars for the 9th annual DSS ATX on Feb 18, where we will focus on GENAI AND INTELLIGENT AGENTS IN THE ENTERPRISE. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/austin/

Kelly discusses how ethical considerations influence machine learning, NLP, and data quality, and how organizations can integrate human-centered thinking into technical decision-making. They also share insights from their upcoming book, The Friendly Guide to Data Science, aimed at making the field accessible, ethical, and practical.

Key Highlights:

• Ethical AI in Practice: How to incorporate ethics and human-centered principles into data science projects.
• Behavioral Economics & Decision-Making: How understanding human behavior informs AI and tech strategies.
• Making Data Science Accessible: Kelly’s approach to mentoring, writing, and teaching the next generation of data scientists.

🎧 Tune in to Episode 58 to hear Kelly Vincent’s insights on ethical AI, data science, and technology for good.

Be sure to mark your calendars for the 7th annual DSS NYC on Dec 11, where we will focus on THE FUTURE OF APPLIED AI IN Finance and Banking. Join us to hear from experts on how AI is shaping the future of the enterprise. https://www.datascience.salon/newyork/

Swarnendu De dives into frameworks like the SaaS Product Success Strategy™ and TechBlueprint Architecture Framework™, and shares insights on turning product ideas into execution-ready roadmaps, designing modular and scalable systems, and creating AI-powered business automation.

Key Highlights:

• Building Scalable SaaS & AI Products: Learn Swarnendu’s approach to designing modular, cloud-native systems that meet investor expectations and real-world demands.
• AI for Business Automation: Discover how AI can be integrated where it drives real value—automating workflows, improving decision-making, and enhancing product experiences.
• Mentoring & Leadership: Insights into coaching tech leaders and founders, aligning technology with business goals, and accelerating team performance.
• From Vision to Execution: Explore Swarnendu’s process for taking a concept through rapid workshops, validation, and execution-ready roadmaps.

🎧 Tune in to Episode 57  to hear how Swarnendu De is turning ideas into high-performing, scalable software products, and creating frameworks and strategies that empower teams, founders, and enterprises alike.

Be sure to mark your calendars for the 3rd annual DSS NYC on Dec 11, where we will focus on GENAI AND INTELLIGENT AGENTS IN FINANCE & BANKING. Join us to hear from experts on how AI is shaping the future of the finance, banking and insurance. https://www.datascience.salon/newyork/