BI has a bad rap as last century’s analytics and static reporting, while AI is the cool kid on the block. Yet most AI projects focus on tech over business impact. With real-time analytics and actionable insights, BI is now focused on driving measurable value across operations, strategy and customer engagement.

As Microsoft continues to promote and enhance their Microsoft Fabric offering, many clients are asking: How does Microsoft Fabric impact my current Power BI estate? What are some strategies for successful deployment of Microsoft Fabric? How do we scale analytics in Microsoft Fabric and leverage its native AI functionality? This session provides expert insights on Power BI to Microsoft Fabric migrations.

As Microsoft continues to promote and enhance their Microsoft Fabric offering, many clients are asking: How does Microsoft Fabric impact my current Power BI estate? What are some strategies for successful deployment of Microsoft Fabric? How do we scale analytics in Microsoft Fabric and leverage its native AI functionality? This session provides expert insights on Power BI to Microsoft Fabric migrations.

This session discusses whether AI will replace business intelligence (BI) or simply transform it. As BI interfaces become gateways to AI analytics, trust and precision are crucial — users won’t tolerate AI errors. Join this session to explore if AI will deepen insights and automate action, or will BI adapt and survive in a changing landscape.

Analytics and business intelligence (ABI) platforms are increasingly integrating AI agents to transform how data is analyzed and insights are delivered. Data and analytics leaders need to proactively understand these shifts to maximize AI's business impact and ensure organizational readiness. Join this session to learn more.

Data quality and data observability tools provide significant capabilities to ensure good data for your BI and AI. Data observability tools give organizations integrated visibility into the health of their data, data pipelines and data landscape. Data quality tools enable business users to manage data at its sources by setting rules and policies. Together, these tools help organizations build a strong foundation in data management for BI and AI initiatives.

Analytics and BI platforms and data Science and machine learning platforms are important technologies that drive insight-driven decision making and allow AI systems to be built and operationalized throughout the enterprise. This session unpacks the Magic Quadrants of both markets and gives inisght on the trends that you should be aware of.