Extracting Value from Unstructured Data – Implementing Text Analytics on the Voice of Student - Wang, Jiangping (Transactions on Engineering and Computing Sciences, 2020)
Unstructured data is chaotic and messy with little or no metadata and lacks of traditional organization structure. However, same as any structured data, unstructured data is also part of valuable business asset. Many times, it is text heavy and needs extensive preprocessing before data mining algorithm can apply for building models in order to reveal value hidden in the data. Text as a form of data is widely used in business operations as a major way of communication, generating increasing volumes of data. Text data in its raw form is relatively dirty. The embedded business value can be extracted through approaches in text mining and text analytics. This paper presents a case study in this general process of revealing value in unstructured data and applying on data collected to support online learning and student assistance.