Analysing enterprise content to support decision making
Project Description
Companies create massive amounts of unstructured content, like documents, e-mails, websites, tweets, images, and audio and video files. The management of that content?especially its storage, retrieval, and retention?has been identified as one of the most prevalent challenges in the digital age. The next challenge is analyzing that content in order to support decision making, for example, to identify patterns and relationships, explain why certain results or events occurred, and predict future trends. Various methods for automatically analyzing unstructured large amounts of content have been proposed over the last years. However, these methods' potential has not yet been fully exploited in research. Most studies have approached data-analytics from a predominantly technical perspective, while only few studies have been dedicated to investigating their application in real-life business contexts. Accordingly, the dissertation project explores how to improve organizational decision making through content analytics in actual business contexts. The dissertation is paper-based, so it will cover a series of research questions and draw from diverse research methodology.
