The January TDWI Virtual Summit has concluded, but on-demand access is available for previously registered attendees through June 1, 2022.

Click the login button below to access all sessions and content.

Join us for an upcoming summit, or check out our full calendar of virtual training opportunities.

By using website you agree to our use of cookies as described in our cookie policy. Learn More

TDWI Virtual Summit

Automation Across the Data and Analytics Lifecycle

January 26–27, 2022

8:30 am - 1:00 pm PT

Empowering Citizen Data Scientists and Engineers: Research Trends and Directions

January 27, 2022

Prerequisite: None

David Stodder

Senior Research Director


Across organizations of all sizes, demand continues to rise for powerful business analytics—for data interactions that can deliver sharp insights about what is happening now, why it is happening, and what is likely to happen in the future. Easier-to-use self-service technologies and cloud-native services are democratizing analytics, opening up more advanced data interaction and modeling to “citizen” data scientists, data engineers, and other professionals—that is, managers, analysts, and other knowledge workers in business functions outside of IT.

Although not as advanced as those of dedicated data scientists and engineers, “citizen” workloads and use cases push beyond traditional business intelligence. The trend is driving growth in scalable and elastic cloud data platforms, which together with self-service data preparation and visualization services are making it possible for citizen data professionals in small and medium-sized organizations to develop deeper data insights to compete with larger organizations.

This talk will discuss TDWI research regarding where things stand and are headed in the future for empowering citizen data scientists and engineers.

Topics will include:

  • Augmentation with AI: The trend toward AI-driven recommendations and smart automation of complex activities such as predictive forecasting and real-time analytics
  • Natural language search and processing to increase speed, collaboration, and ease of interaction with relevant data and artifacts such as visualizations and reports
  • How data catalogs are using AI-driven automation to reduce manual work, make it easier to find and share data sets, and improve data quality
  • Self-service data preparation and pipeline development trends and directions
  • Human and organizational factors: Data literacy and balancing self-service with enterprise governance and security

Subscribe to Receive Summit Updates via Email