Tracks:
Keynote
Keynote proposals for this event should be engaging. The keynote should set the tone for the day and inspire attendees to move their organizations toward a more data-driven culture stemming from the advantages of applying data analytics. Speakers should inspire attendees to attend the tracks and sessions throughout the day. Keynote presentations should set the tone for a day of focus on the tracks of the summit:
- Track 1: Data Story Telling and Visualization
- Track 2: The Artificial Intelligence Continuum: from Robotic Program Automation to Deep Learning
- Track 3: Data Management, Governance & Privacy
- Track 4: Data Analytics: business intelligence, modeling and applications of big data
Track 1: Data Story Telling and Visualization
Proposals for this track can include topics that demonstrate the value of data storytelling, visualization or give significant value in the creation of these techniques. Proposals may answer the questions why they are important and how they inspire action. The use of case studies and specific examples of organizations using these techniques is encouraged.
Track 2: The Artificial Intelligence Continuum: from Robotic Program Automation to Deep Learning
Seeking proposals with demonstrated examples of how organizations have employed AI and RPA to enhance processes, reduce costs, and improve delivery of service. Use cases illustrating the applications of Machine Learning and Deep Learning are strongly encouraged.
Track 3: Data Management, Governance & Privacy
Proposals should address the importance of not only managing data but ensuring security and best practices for implementing data systems that meet the regulatory and functional needs of organizations. Case studies and program implementations for meeting the ever-changing data regulations organizations are facing are encouraged.
Track 4: Data Analytics: Business Intelligence, Modeling and applications of Big Data
Proposals for this track should address not just data but how it is modeled and how it is applied for better outcomes. How do we harness the value and insights from the data we collect? What are the best practices, tools and training processes that organizations must implement amidst a changing landscape of regulation.