Data & analytics leaders can deliver increasing value to their organizations. This session will uncover new research and trends which will enable you to find new powerful ways to connect with stakeholders, address skills shortages and build trust to overcome cultural resistance to change. Learn how to attract and retain a world-class D&A team and lead with purpose to ensure the data-driven transformation required for success.

Organizations that lack a governance framework for self-service can struggle to maintain control as work becomes chaotic, siloed and inconsistent. This session will allow you to engage with a Gartner expert who will dive into the capabilities and features of popular A&BI tools and provide actionable advice on how these can be leveraged to govern data and analytics within self-service initiatives.

Many organizations today are experiencing expanding portfolios of analytics tooling. Tools with overlapping capabilities create opportunities for data duplication, siloes and inconsistencies in metrics. Organizations should simplify their analytics architecture by performing a rationalization and consolidation exercise. This reduces the burden on IT to support multiple tools and govern analytics.

Productionizing ML models remains a significant challenge for enterprises as they scale ML operations to hundreds or thousands of models. These organizations benefit from implementing a logical feature store to manage data for ML. Logical feature stores accelerate time to production and promote feature reusability, reproducibility and reliability.