David Stodder
Saptarshi Sengupta
TDWI research finds that data democratization—empowering a broader spectrum of people with self-service data access, exploration, preparation, and analytics—is a top priority. Self-service business intelligence and analytics are central to transforming daily operational decisions as well as forecasting and higher-level strategies.
Today, citizen data scientists are pushing beyond data consumption to perform more advanced data discovery and predictive analytics. Developers are upgrading business 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.
Yet without a thoughtful strategy, users will be frustrated by their inability to find, prepare, and interact with all the data they need amid the complexity of today’s distributed environments. Adding to existing data silos, ongoing cloud migrations are locating data in hybrid environments both on premises and frequently on multiple cloud platforms. Changes in business structures also create data confusion and bottlenecks. Data acquisition and preparation are too often slow, manual, and error-prone.
Join this TDWI Expert Panel to learn about technology trends and best practices for improving data democratization to increase business value. Topics we plan to discuss include:
- Making data complexity transparent to users and eliminating data access bottlenecks
- Modernizing data architectures to overcome user frustration with data silos and distributed data
- Balancing self-service analytics with requirements for data governance, quality, and security
- The role of data catalogs and metadata integration in data democratization
- Data literacy and building a strong data culture to increase the value of data democratization
