On-Demand Webinar
Cotton inc. and SAS in conjunction with the NCGA present:
• Cost: Complimentary
Machine failure during Ginning Season can be catastrophic. Applying analytics to data that Gin Mills are already collecting can alert you to possible machine failures before it happen. SAS, Cotton inc., and the NCGA have been working together to explore how SAS Preventative Maintenance technology that’s already being used in other industries can be applied in the Ginning industry. Join us as we share insights extrapolated from Gin Mills and walk you through the SAS Preventative Maintenance solution.
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Emily has been driving digital solutions to help businesses achieve critical initiatives for over 15 years. Passionate about providing the best possible solution at the right time with gold standard customer service is how she’s achieved customer success year after year. Emily has worked with some of the largest tech firms, to some of the smallest start ups ensuring their digital transformation is a fruitful one.
Dr. John Gottula is an AgTech innovator with an applied crop science background and a passion for analytics. John’s undergraduate research at Texas Tech University focused on cotton crop physiology; subsequently he became the cotton crop lead at Bayer Crop Science Regulatory Sciences division. Now working at SAS, John is the co-creator of #AgileAg, a movement to link Agile processes with crop science to drive analytics adoption across the agriculture sector.
Dr. Barnes is Senior Director of Agricultural and Environmental Research at Cotton Incorporated where for the last eighteen years he has managed agricultural engineering related projects, including programs on: precision farming, ginning, irrigation management, conservation tillage, and cotton harvest systems. He has also served as a team member in documenting cotton’s progress in reducing its environmental footprint while at the same time increasing productivity. Most recently he has been leading efforts to increase the automation of cotton production systems.
Jordan is a Senior Associate Systems Engineer at SAS and is currently pursuing a Master’s of Advanced Analytics at West Virginia University. She focuses on the use of advanced analytics and machine learning techniques to help clients from a wide range of industries make better decisions with their data, faster. A native of Pennsylvania, she is based out of SAS’ world headquarters in Cary, North Carolina.