DATAG 2026 Summer Conference

Enterprises and developers are increasingly faced with a choice: rely on corporate AI services that ship convenience but also data‑exfiltration risk, or host sophisticated models locally for full control and cost predictability. This session walks you through the entire decision‑making pipeline—from hardware sizing to software orchestration—so you can deploy, query, and continuously improve open‑source large language models (LLMs) on‑premise.

Numbers help us make sense of the world but understanding what they really mean isn't always straightforward. In this interactive session, participants will explore how context, framing, and human intuition shape our understanding of data. We’ll unpack why some numbers surprise us and learn practical strategies for making numbers more meaningful, communicable, and useful in decision-making.

Data leadership is most powerful when it centers equity, relationships, and belonging.
This session is designed for district and school leaders seeking to leverage data in culturally and linguistically sustaining ways to strengthen student attendance and deepen home–school communication.
Participants will explore how equity-based data practices can move beyond compliance to become tools for connection, trust-building, and shared accountability with families. Using real-world examples, the session highlights how platforms such as ClassDojo and Attendance Point can be strategically aligned with inclusive communication practices, multilingual engagement, and culturally responsive outreach.
Attendees will learn how to:

Use attendance data as an early engagement signal, not a punitive measure
Align data practices with culturally and linguistically sustaining leadership principles
Strengthen two-way family communication through accessible, relationship-centered tools
Support student success by connecting attendance trends to family voice and community context

This session equips data leaders with practical strategies, reflective prompts, and actionable takeaways to ensure data systems support equity, partnership, and improved outcomes for all students.

In this session, we will review the key steps in the English Language Leaner identification process, including the NYSITELL and NYSESLAT.

Protecting student data is everyone’s responsibility. This session distills the core requirements into clear and practical actions. The participants will learn how to avoid common missteps, strengthen compliance, and prevent breaches. Learn how a simple pause before sharing can make all the difference in safeguarding student information.