Big-Data Labs: Merchandising Informatics by Using Hyperlinks and Network Analysis Visualization Approaches
Abstract
Merchandising informatics, a novel research-related pedagogy, views data analytics from an information management perspective on merchandising practices. More willingly competent merchandising graduates are able to provide analytical support to cross functional projects (e.g., email targeting, consumer recommendations, product loyalty forecasts) and assist in building large data sets from multiple sources in order to predict future data characteristics. A visionary data inventor with a passion for learning new technologies and translating data into business solutions is critical for growth and success in the merchandising industry.
Merchandising informatics aims to transform teaching and learning at graduate courses and around the globe by implementing big-data labs. Applying hyperlinks and Network Analysis Visualization (NAV) approaches to big data construal helps graduates grasp contemporarily big data concepts more quickly and fully, connect theory and application more adeptly, and engage in learning more readily, while also improving instructional techniques, and facilitating the widespread sharing of knowledge. Indeed, the information management perspective and practical experiences within merchandising informatics equip graduates with unique and career-oriented capabilities.
How to Cite:
Kim, H., (2018) “Big-Data Labs: Merchandising Informatics by Using Hyperlinks and Network Analysis Visualization Approaches”, International Textile and Apparel Association Annual Conference Proceedings 75(1).
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