Using Python with Proprietary Compute Power to Leverage Big Data Analytics
E145 | Sun 16 Jul 2 p.m.–3 p.m.
Presented by
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Joseph Castle, PhD
@https://twitter
https://www.linkedin.com/in/jrcastle/
Dr. Castle builds strategic relationships with the U.S. public sector with SAS. This involves educating current and potential customers about data analytics, artificial intelligence (AI), machine learning (ML), cloud-based environments, development operations (DevOps), and open source software (OSS).
Dr. Castle served over twenty years in the U.S. federal government. In the General Services Administration (GSA), he led numerous programs for the office of the Chief Information Officer and Technology Transformation Services. Highlights included forming and managing the GSA Digital Service, a high-performing technology team who implemented federal digital government strategy initiatives: open government, data, and code. He directed the federal government’s Open Source Program Office (OSPO), or Code.gov, to implement the federal source code policy by educating and collaborating with cabinet-level federal agencies to publish OSS. He also served in the Obama Administration at The White House in the Office of Management and Budget (OMB). A veteran, Dr. Castle served in the U.S. Army’s 10th Mountain Division. He is a Fed100 recipient and a GitHub Star.
Dr. Castle holds numerous advanced academic degrees including an MBA, MS in information systems, and a PhD in public administration and public affairs. He lives in Maryland with his wife and two children.
Joseph Castle, PhD
@https://twitter
https://www.linkedin.com/in/jrcastle/
Abstract
Organizations rely on computer software to aid in the accurate and timely analysis of data. Open source software (OSS) is becoming more prevalent in all organizations from academia to industry to government. Utilizing Python with proprietary compute power (e.g., SAS Viya) enables users of all levels to apply advanced analytics, data visualizations, and complex statistical modeling capabilities to aspects of the analytics lifecycle, producing descriptive and predictive data artifacts.
This session will provide an overview of OSS with proprietary compute power as it pertains to business organizational analysis, the analytics lifecycle, and it gives participants a better understanding of how to leverage software for higher quality decision making.
Organizations rely on computer software to aid in the accurate and timely analysis of data. Open source software (OSS) is becoming more prevalent in all organizations from academia to industry to government. Utilizing Python with proprietary compute power (e.g., SAS Viya) enables users of all levels to apply advanced analytics, data visualizations, and complex statistical modeling capabilities to aspects of the analytics lifecycle, producing descriptive and predictive data artifacts. This session will provide an overview of OSS with proprietary compute power as it pertains to business organizational analysis, the analytics lifecycle, and it gives participants a better understanding of how to leverage software for higher quality decision making.