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Enterprises use a wide range of heterogeneous information systems in their business activities such as Enterprise Resource Planning (ERP), Customer Relationships Management (CRM) and Supply Chain Management (SCM) systems. In addition to the large amounts of heterogeneous data produced by those systems, external data is an important resource that can be leveraged to enable taking quick and rational business decisions. Classic Business Intelligence (BI) and even the newer Agile Visualization tools focus much of their selling features on attractive and unique visualizations. Preparing data for those visualizations still remains the far most challenging task in most BI projects large and small. Self-service data provisioning aims at tackling this problem by providing intuitive datasets discovery, data acquisition and integration techniques to the end user.

The goal of this thesis is to provide a framework that enables self-service data provisioning in the enterprise. This framework empowers business users to search, inspect and reuse data through semantically enriched datasets profiles. Publicly available datasets contain knowledge from various domains such as encyclopedic, government, geographic, entertainment and so on. The increasing diversity of these datasets makes it difficult to annotate them with a fixed number of predefined tags. Moreover, manually entered tags are subjective and may not capture their essence and breadth. We propose a mechanism to automatically attach meta information to data objects by leveraging knowledge bases like DBpedia and Freebase which facilitates data search and acquisition for business users …