TDWI’s esteemed Modern Data Leader’s Summit Advisory Board is currently looking for experienced practitioners like you who would like to share their expertise, best practices, and passion with TDWI’s community of data, analytics, and AI professionals.

We are currently planning our Modern Data Leader’s Summit on Analytics and AI to be held October 21-23, 2024, in Orlando, Florida. This in-person summit will attract analytics, AI, and data leaders who are interested in solving challenges, organizing to execute, and moving faster to achieve business objectives.

Our goal is to provide insightful and impactful content that focuses on providing frameworks and approaches to maximize the value of data to improve customer marketing and engagement, increase operational efficiency and effectiveness, innovate with new products and services, and realize better business outcomes.

Presentation Formats:

• Case Studies: Share real-world experiences and outcomes in 40-minute presentations.
• Expert Presentations: Deep dive into a topic with 1-hour expert-led discussion.

Presentation topics of interest:

• How your organization accomplished business objectives with analytics and AI; how you handle challenges and sustain growth
• Data strategies for ensuring the appropriate data infrastructure and environment to support analytics and AI growth; using technologies such as vector databases
• Large language models (LLMs) and generative AI: Strategies for success and avoiding potential pitfalls
• Natural language processing and text analytics
• Getting the most from diverse data (structured, semi-structured, and unstructured)
• Real-time analytics and data streaming use cases and strategies
• Organizing to execute, including using methodologies such as MLOps, DevOps and DataOps to scale, accelerate deployment, and continuously improve quality
• Empowering all kinds of users with self-service analytics, data access, pipelines, and data curation capabilities; AI augmentation of business intelligence
• Balancing self-service BI, analytics, and data science with enterprise data and AI governance priorities
• Analytics and AI frameworks and best practices; governance for AI explainability and AI ethics; integrating data and AI governance
• Using data intelligence, including data catalogs, master data management, data lineage, semantic data integration, knowledge graphs, and more to support analytics and AI
• People issues: chief analytics officer, chief information officer, and chief data officer priorities for organizing teams, handling change management, and meeting goals

Note to Solution Providers: We encourage you to nominate your customers for case study presentations.

Submissions may also be considered for future TDWI educational events.