This paper investigates how the company Westinghouse Electric Company works with data cleansing and data migration. The main purpose with the paper is to give suggestions to Westinghouse on things they need to consider when cleansing and migrating data. The study describes strategies that are used when working with data cleansing and data migration, and describes common pitfalls and problems that can occur. This information has been collected through a literature study, where books and scientific papers on the matter have been collected and revised.
By interviewing the developers that are working with data cleansing and data migration at Westinghouse, I could get an understanding of their work processes. Semi structured interviews where conducted, and the result was analyzed by connecting the theoretical framework to the empirical data. The analysis focuses on finding flaws and areas to improve at Westinghouse.
Finally, the paper shows different flaws Westinghouse has, such as missing strategies on how to work and in many cases failing to engage the business, and how they could prevent them.