Introduction
While big data has been a topic of research and industry activity, much of it has been focused on unstructured data such as web logs, web crawl data, and social media data. One area which has received less attention but offers significant opportunities is enterprise big data. As companies drive towards leveraging analytics to create new value, they are faced with one of the most daunting challenges: How can we link data from hundreds of business processes, tens of businesses, and combine relevant enterprise data with external data to enable novel analytical insights? Consequently, Enterprise Big Data Semantics, Analytics and Modeling (EBDSAM) is an emerging area of research. This workshop will share key challenges in EBDSAM, novel approaches to solutions, and new business challenges that can be addressed by big data semantic and analytics modeling.
Call for paper
Submission Topics
Workshop papers can fall into any of the following categories involving exploiting of enterprise big data and / or enterprise applications:
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Natural Language Processing in business analytics
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Use of big data to estimate employee value
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Machine learning for financial planning
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Workforce optimization and skill mix strategy - use of big data to understand which teams or types of employees complement each other and work well together
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Internal company recommendation engines
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Selection of products and offerings to maximize profit
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Salesforce optimization
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Initiatives that use big data to understand and develop employee skillsets
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Use of big data to determine when/how to use various marketing and sales channels
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Challenges in organizing enterprise big data from a variety of internal sources
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Challenges of combining internal organization data with external data (for example, dealing with unique internal taxonomies)
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Additional related categories not covered above
All Comments
Important Date
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Dec 11
2017
Conference Date
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Dec 11 2017
Registration deadline
Sponsored By
Contact Information
- Prof. Xiaohua Tony Hu
- xh******@drexel.edu
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