BIG DATA, DATA SCIENCE AND ANALYTICS MANAGEMENT, GOVERNANCE AND COMPLIANCE MINITRACK
This minitrack welcomes submissions of original work addressing challenges, theoretical lenses, frameworks, development, evaluation, and impact studies assessing the implications of Big Data, data science and analytics management, governance, and compliance. We also encourage submissions of research-in-progress as well as those that are practically oriented yet have the potential to make significant contributions to the research community.
Relevant topics for the minitrack include, but are not limited to, the following:
- Innovative Big Data, data science and analytics governance approaches
- Chief Data Officer and Chief Analytics Officer roles and responsibilities
- Data, analytical model and algorithm asset management
- Analytics workflow management
- Analytic model life-cycle management
- Model management platform design
- Model compliance management
- Model documentation
- Ethics of data analytics
- Analytics regulatory risks and risk mitigation
- Data and model transparency
- Business value of analytics governance
- Platform economics and strategy
- Coordinate IT, analytic and client teams
- Analytics documentation and metadata design
- Legal implications of analytics governance policies
- Organizational implications of advances in the field of legal analytics
- Managing and deploying champion and challenger models
- Campaign documentation and model reuse
- Data and model ownership and contracts
Minitrack Co-Chairs:
Michael Goul (Primary Contact)
Arizona State University
Michael.Goul@asu.edu
Zhongju Zhang
Arizona State University
Zhongju.Zhang@asu.edu
Jeffrey Saltz
Syracuse University
jsaltz@syr.edu
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Zhongju Zhang
Arizona State University
Tempe AZ
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