Paradime is the pioneer in building the 'Cursor for Data' - a platform for the AI-enabled analytics engineer to achieve 10x productivity. In this lighting talk, we will showcase how Paradime and DinoAI is changing the way analytics engineering is done.

This talk will explore how NVIDIA Blueprints are accelerating AI development and deployment across various industries, with a focus on building intelligent video analytics agents. Powered by generative AI, vision-language models (VLMs), large language models (LLMs), and NVIDIA NIM Microservices, these agents can be directed through natural language to perform tasks such as video summarization, visual question answering, and real-time alerts. This talk will show how VSS accelerates insight from video, helping industries transform footage into accurate, actionable intelligence.

Learn how to transform your data warehouse for AI/LLM readiness while making advanced analytics accessible to all team members, regardless of technical expertise. 

We'll share practical approaches to adapting data infrastructure and building user-friendly AI tools that lower the barrier to entry for sophisticated analysis. 

Key takeaways include implementation best practices, challenges encountered, and strategies for balancing technical requirements with user accessibility. Ideal for data teams looking to democratize AI-powered analytics in their organization.

In travel, every second counts and missed signals can mean missed opportunities. This expert panel of Women in Data® leaders will explore how real-time analytics is reshaping decision-making across the travel industry at every stage, from streamlining internal operations to improving the passenger experience.  

Whether you're taking your proverbial first steps or are light years ahead leading your own data team, we can guarantee there will be something for everyone to connect to and reflect on whilst also discovering how live insights are helping drive data-led decision makers to act faster, smarter, and with greater impact.

Powered by Women in Data®

Legacy data tools weren’t built for the AI era. Agentic Data Management replaces static rules and siloed platforms with intelligent agents that monitor, reason, and act—automating quality, governance, and lineage at scale. Discover how data leaders are shifting from manual firefighting to autonomous control, powering faster, trusted, and scalable data for AI and analytics.

- See a live demo of an agentic system in action

- Learn how probabilistic and deterministic approaches work in concert

- Explore how to build intelligent data products using the MCP protocol

As enterprises scale their deployment of Generative AI (Gen AI), a central constraint has come into focus: the primary limitation is no longer model capability, but data infrastructure. Existing platforms, optimized for human interpretation and batch-oriented analytics, are misaligned with the operational realities of autonomous agents that consume, reason over, and act upon data continuously at machine scale. 

In this talk, Zhamak Dehghani — originator of the Data Mesh and a leading advocate for decentralized data architectures — presents a framework for data infrastructure designed explicitly for the AI-native era. She identifies the foundational capabilities required by Gen AI applications: embedded semantics, runtime computational policy enforcement, agent-centric, context-driven discovery.

The session contrasts the architectural demands of AI with the limitations of today’s fragmented, pipeline-driven systems—systems that rely heavily on human intervention and customized orchestration. Dehghani introduces autonomous data products as the next evolution: self-contained, self-governing services that continuously sense and respond to their environment. She offers an architectural deep dive and showcases their power with real-world use cases.  

Attendees will learn the architecture of “Data 3.0”, and how to both use GenAI to transform to this new architecture, and how this new architecture serves GenAI agents at scale.

Join Sami Hero and Tammie Coles, as they share how Ellie is reinventing data modeling with AI-native tools that empower both technical and non-technical users. With CData Embedded Cloud, Ellie brings live metadata and data models from systems like Snowflake, Databricks, and Oracle Financials into a unified modeling workspace. Their platform translates legacy structures into human-readable insights, letting users interact with a copilot-style assistant to discover, refine, and maintain data models faster—with less reliance on analysts.

You’ll see how Ellie uses generative AI to recommend new entities, reconcile differences between models and live systems, and continuously document evolving data environments. Learn how corporations are using Ellie and CData together to scale high-quality data modeling across teams. reducing rework, accelerating delivery of analytics-ready models, and making enterprise architecture accessible to the business.

Data leaders today face a familiar challenge: complex pipelines, duplicated systems, and spiraling infrastructure costs. Standardizing around Kafka for real-time and Iceberg for large-scale analytics has gone some way towards addressing this but still requires separate stacks, leaving teams to stitch them together at high expense and risk.

This talk will explore how Kafka and Iceberg together form a new foundation for data infrastructure. One that unifies streaming and analytics into a single, cost-efficient layer. By standardizing on these open technologies, organizations can reduce data duplication, simplify governance, and unlock both instant insights and long-term value from the same platform.

You will come away with a clear understanding of why this convergence is reshaping the industry, how it lowers operational risk, and advantages it offers for building durable, future-proof data capabilities.

Business leaders are demanding clear evidence that data investments are generating real business value — not just summaries of how many dashboards or datasets live in your analytics environment. This session will equip you with practical, proven methods — like business value maps and usage analytics — to uncover, measure, and clearly communicate the true business impact of your data and analytics initiatives. You’ll leave with the tools and language you need to lead ROI conversations, defend your strategy, and secure ongoing investment.

In an era where data drives decisions, Knight Frank is redefining what it means to be in property with purpose. This session explores how Knight Frank harnesses the power of big data not just to optimise real estate strategies, but to create meaningful social impact across communities. From urban regeneration to inclusive housing initiatives, data is at the heart of their mission to build a better future.

A key highlight of the talk will be Knight Frank’s collaboration with Girls in Data, a pioneering initiative aimed at empowering young women to pursue careers in data and analytics. Through mentorship, workshops, and hands-on experience, Knight Frank is helping to close the gender gap in tech and foster the next generation of data leaders.

Join us to discover how data can be a force for good, driving equity, opportunity, and transformation in the property sector and beyond.

Powered by: Women in Data®

How do you prepare a global industrial business for AI? At Secil, the answer was data governance. In this session, Ricardo Carvalho shares how the team replaced siloed systems with a unified data platform using Domo, delivering enterprise-level analytics, smarter operations, and a foundation for scalable AI that drives real outcomes in just 18 months.

In an era where data is central to business success, the demand for skilled analysts continues to outpace supply. This session explores how data analytics apprenticeships offer a dynamic, practical solution to the widening skills gap, equipping individuals with industry-relevant experience while delivering immediate value to employers.

Using the NowSkills apprenticeship model as a case study, this session will showcase how a well-rounded curriculum—combining technical training, real-world projects, and structured mentorship—can transform aspiring analysts into confident, capable professionals. Attendees will gain insights into how these programmes adapt to diverse learning needs, integrate business challenges, and embed workplace-ready skills from day one.

Through success stories and data-driven outcomes, the presentation will highlight the benefits for both individuals and organisations: from faster onboarding and increased employee engagement to improved innovation and retention. Additionally, apprenticeships contribute to greater diversity and inclusion by widening access to digital careers beyond traditional academic routes.

Attendees will leave with practical strategies to implement or enhance apprenticeship programmes, identify future skills, and collaborate effectively

Data is one of the most valuable assets in any organisation, but accessing and analysing it has been limited to technical experts. Business users often rely on predefined dashboards and data teams to extract insights, creating bottlenecks and slowing decision-making.

This is changing with the rise of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). These technologies are redefining how organisations interact with data, allowing users to ask complex questions in natural language and receive accurate, real-time insights without needing deep technical expertise.

In this session, I’ll explore how LLMs and RAG are driving true data democratisation by making analytics accessible to everyone, enabling real-time insights with AI-powered search and retrieval and overcoming traditional barriers like SQL, BI tool complexity, and rigid reporting structures.

The world has never been more connected. Today, customers demand near-perfect uptime, responsive networks, and personalized digital experiences from their telecommunications providers. 

The industry has reached an inflection point. Legacy architectures, fragmented customer data, and batch-based analytics are no longer sufficient. Now is the time for Telcos to embrace real-time, when the speed of insights and the ability to remain agile determine competitive advantage.

In this session, leaders from Orange Belgium, Google Cloud, and Striim explore how telcos can rethink their data foundations to become real-time, intelligence-driven enterprises. From centralizing data in BigQuery and Spanner to enabling dynamic customer engagement and scalable operations, Orange Belgium shares how its cloud-first strategy is enabling agility, trust, and innovation.

This isn’t just a story of technology migration—it’s about building a data culture that prioritizes immediacy, empathy, and evolution. Join us for a forward-looking conversation on how telcos can align infrastructure, intelligence, and customer intent.

In an era where sustainability is no longer optional but essential, data-driven organisations are leveraging advanced analytics to unlock new pathways for innovation and growth.  

This 30-minute session brings together leading Women in Data® experts with deep experience in applying sustainability analytics across sectors. Through real-world insights and strategic frameworks, they will explore how environmental, social, and governance (ESG) data can be harnessed to inform smarter decision-making, uncover hidden opportunities, and drive long-term value creation and innovation whist remaining rooted in responsible data use.

Powered by: Women in Data®

Discover how to build a powerful AI Lakehouse and unified data fabric natively on Google Cloud. Leverage BigQuery's serverless scale and robust analytics capabilities as the core, seamlessly integrating open data formats with Apache Iceberg and efficient processing using managed Spark environments like Dataproc. Explore the essential components of this modern data environment, including data architecture best practices, robust integration strategies, high data quality assurance, and efficient metadata management with Google Cloud Data Catalog. Learn how Google Cloud's comprehensive ecosystem accelerates advanced analytics, preparing your data for sophisticated machine learning initiatives and enabling direct connection to services like Vertex AI. 

Learn how Tableau helps organisations manage uncertainties and go from data to decisions faster. Join us on this agentic journey, empowering

 Learn how Tableau helps organisations manage uncertainties and go from data to decisions faster. Join us on this agentic journey, empowering every data professional to deliver limitless success.

Session brought to you by Salesforce

In this session, Omni CEO Colin Zima and VP of Product Arielle Strong will share how early experiments led to AI features our customers actually use and love: from natural language chat, to embeddable AI products, to APIs and an MCP server. 

They’ll walk through what worked, what didn’t, and how AI has reshaped our product roadmap. Expect real-world examples of AI analytics in production, along with best practices for getting your data AI-ready.

For years, data engineering was a story of predictable pipelines: move data from point A to point B. But AI just hit the reset button on our entire field. Now, we're all staring into the void, wondering what's next. While the fundamentals haven't changed, data remains challenging in the traditional areas of data governance, data management, and data modeling, which still present challenges. Everything else is up for grabs.

This talk will cut through the noise and explore the future of data engineering in an AI-driven world. We'll examine how team structures will evolve, why agentic workflows and real-time systems are becoming non-negotiable, and how our focus must shift from building dashboards and analytics to architecting for automated action. The reset button has been pushed. It's time for us to invent the future of our industry.