A data warehouse solution emphasizing the use in geographic information systems

This paper will explore use of a data warehouse solution for an electric utility that generates and transmits power across four US states. The pseudonym “Utility “X”” will be used to represent the electric utility for security reasons. At Utility “X” several systems store information that is managed in silos that, in some cases, operate on proprietary database formats. This type of usage is identified as a barrier in the development of an enterprise-wide data source. A data warehouse can ultimately help to bridge the Utility “X” information gap, and provide added accessibility for the company to further develop technology, such as Geographic Information Systems (GIS). The use of a data warehouse can create an environment that increases the usability and accessibility of data. This project will focus on a method of using a data hub; data warehouse; and extract, transform, and load (ETL) processes to compile data from the proprietary equipment maintenance database, the meter system database, and the plant information database to provide one cohesive dataset in a data warehouse, which would ensure easier access to sets of processed electric meter data. The combination of these three sources offers advantages to other departments within the company that need meter information. A data warehouse does not require alteration of source systems that would cause deviation from their primary functions. For example, when a data warehouse solution is not used, there is pressure for existing databases to conform to new uses, such as GIS applications. This adaptation can include costly new system changes, database changes, and interface changes. However, a system that is set up for one purpose might also contain data that is useful for another purpose. By leveraging a data warehouse solution and developing a new use of the existing data, the company can avoid changing the current system configuration. This research will define an approach to building a data warehouse based on qualitative action research methods. Research was conducted at the company by using an iterative interview process wherein information from interviews was gathered and classified based on information from primary sources on the topic of data warehousing. An example using electric meter data from the company was identified that showed several solutions to problems by use of a data warehouse environment.