Data and Analytics - Driving Mission Value

Government and industry organizations utilize data to create superior products and services, streamline operations for cost savings and respond to customer needs and expectations.

Emerging data trends include:

• Data-as-a-Service. As the future collaboration expands beyond the enterprise, the need to share governed data, models and insights within the same agency or organization is growing exponentially, prompting both government and industry to move toward a data-as-a service platform
• Autonomous AI. The introduction of machine learning, generative AI, natural language processing and other techniques are moving towards automatic generated analytic reports at a much faster pace
• Synthetic Data. To respond to security and privacy issues, there is interest in offering synthetic data for any given use case models. Synthetic data also aids in developing comprehensive training data sets
• Data Democratization – The ongoing process of enabling everybody in the organization regardless of their technical expertise to work with data comfortably, make data-informed decisions, and build customer experiences powered by data
• Data Governance. Enterprise analytics to drive business strategies and actions can only occur with thoughtful and scalable governance.

This forum will include subject matter experts from government, industry, and academia to address the emerging data trends occurring today and in the future. The trends, successes, challenges, outcomes, and case studies will provide an in-depth view of why data is important in decision making, how it is being used with what is working, and the future plans for data use in government and industry.

OBJECTIVES:

• Learn how government and industry are governing, exploring, and utilizing data to make future business decisions
• Understand the impact of machine learning, artificial intelligence, and other tools on data and data decisions
• Hear what steps are being taken to ensure data privacy and security
• Hear about the needs, issues, transparency, and access, for the workforce in the data ecosystem