Dane Woody
About Dane Woody
Dane Woody is a Data Design and BI Developer at General Motors, currently working at Aquent since 2020. He holds an MBA from Wayne State University and has extensive experience in data visualization, engineering, and various data tools.
Work at Aquent
Dane Woody has been employed at Aquent as a Data Design and BI Developer for General Motors since 2020. His role involves utilizing advanced data design techniques and business intelligence strategies to support General Motors' data initiatives. Based in Detroit, MI, he has contributed to various projects that leverage data visualization and analytics to enhance decision-making processes within the organization.
Previous Experience
Before joining Aquent, Dane Woody held several positions that contributed to his expertise in data analysis and business intelligence. He worked as a Senior Sales Performance Analyst at Ally for five months in 2020. Prior to that, he served as a Project Manager at AMCI for nine months in 2015-2016, and as a Data Analyst at Spark Foundry for two years from 2017 to 2019. He also worked as a Digital Consultant at Shift Digital for one year in 2016-2017.
Education and Expertise
Dane Woody earned his Master of Business Administration (M.B.A.) in Information Systems Management from Wayne State University's Mike Ilitch School of Business, completing his studies from 2015 to 2018. He also holds a Bachelor of Science (B.S.) in Psychology and Exercise Science from Central Michigan University, which he completed from 2008 to 2013. His educational background supports his expertise in data tools and technologies, including Hadoop, Datorama, and Google Analytics.
Technical Skills
Dane Woody possesses advanced skills in various data-related technologies and tools. He extensively utilizes the Microsoft Power Suite for data visualization and business intelligence tasks. Additionally, he has experience with Microsoft Azure for cloud-based data solutions. His skill set includes data engineering, data migration, and data modeling, which are essential for developing effective data strategies.