Data democratization empowers a broader spectrum of people with self-service data access, exploration, preparation, and analytics. Self-service business intelligence and analytics are central to transforming daily operational decisions and business strategies, but they require complicated enterprise data governance and data quality processes to be successful.
Today, citizen data scientists are pushing beyond data consumption to perform more advanced data discovery and predictive analytics. Developers are upgrading applications by embedding visualization and analytics capabilities. Artificial intelligence and machine learning technologies (AI/ML) are playing a role through augmentation to enable better and faster decisions based on larger and more diverse data sets. The emergence of large language models (LLMs) and generative AI will bring even more dramatic changes to user experiences.
This session will focus on trends shaping the future of data democratization. It will discuss key issues for enabling users to be productive and collaborate effectively with trusted, high-quality data. Topics will include:
- The critical role of data intelligence, semantic layers, and data catalogs
- Technology trends that accelerate data insights to deliver business value
- How AI-driven augmentation is taking shape, including with LLMs and generative AI
- Strategies for addressing data governance pain points in the era of data democratization