The data delivery architectures in most enterprises are complex and under documented. Conceptual business models and business analytics applications are created to provide a simplified, and easy to navigate view of enterprise data for analysts. But the construction of such interfaces is tedious, manually intensive to build, requiring specialized technical expertise, and it is especially difficult to map exactly where data came from in the organization. In this paper we investigate how two aspects (lineage and requests for data i.e. semantics and new reports) can be addressed by tying metadata documentation to a systematic data delivery architecture in order to support business analytics applications. We propose a tool framework that includes a metadata repository for each step in the data delivery architecture, a web based interface to access and manage that repository and mapping tools that capture data lineage to support step by step automation of data delivery.

The data delivery architectures in most enterprises are complex and under documented. Conceptual business models and business analytics applications are created to provide a simplified, and easy to navigate view of enterprise data for analysts. But the construction of such interfaces is tedious, manually intensive to build, requiring specialized technical expertise, and it is especially difficult to map exactly where data came from in the organization. In this paper we investigate how two aspects (lineage and requests for data i.e. semantics and new reports) can be addressed by tying metadata documentation to a systematic data delivery architecture in order to support business analytics applications. We propose a tool framework that includes a metadata repository for each step in the data delivery architecture, a web based interface to access and manage that repository and mapping tools that capture data lineage to support step by step automation of data delivery.

The data delivery architectures in most enterprises are complex and under documented. Conceptual business models and business analytics applications are created to provide a simplified, and easy to navigate view of enterprise data for analysts. But the construction of such interfaces is tedious, manually intensive to build, requiring specialized technical expertise, and it is especially difficult to map exactly where data came from in the organization. In this paper we investigate how two aspects (lineage and requests for data i.e. semantics and new reports) can be addressed by tying metadata documentation to a systematic data delivery architecture in order to support business analytics applications. We propose a tool framework that includes a metadata repository for each step in the data delivery architecture, a web based interface to access and manage that repository and mapping tools that capture data lineage to support step by step automation of data delivery.

The data delivery architectures in most enterprises are complex and under documented. Conceptual business models and business analytics applications are created to provide a simplified, and easy to navigate view of enterprise data for analysts. But the construction of such interfaces is tedious, manually intensive to build, requiring specialized technical expertise, and it is especially difficult to map exactly where data came from in the organization. In this paper we investigate how two aspects (lineage and requests for data i.e. semantics and new reports) can be addressed by tying metadata documentation to a systematic data delivery architecture in order to support business analytics applications. We propose a tool framework that includes a metadata repository for each step in the data delivery architecture, a web based interface to access and manage that repository and mapping tools that capture data lineage to support step by step automation of data delivery.