Read the St$.$ Rita's vignettes $($green boxes$)$ on pages $172,181-182,$ and $184.$

The case study begins with Val reminding the EIM team on its primary charge: developing a proposal about the efficacy of an EIM program at St$.$ Rita's. This small dialogue refocuses the students' attention on the bigger picture, keeping in mind that EIM is bigger than the current domain being examined. Data quality challenges and their consequences are introduced in the first vignette when Shirlee and Monte remind the team about quality problems in the MPI and how interfaces with multiple systems are complicated by poor quality master data. In further chapter vignettes, Shirlee and Monte connect the dots between the relationships among master data management, metadata management, and data architecture and begin to see how these subsystems are dependent upon each other. In the final vignette, the EIM team acknowledges that cleansing master data is a back$-$end process and, if more focus was put on gathering better requirements, developing data models, and designing systems, data quality would be better. In the end, the EIM team unanimously agrees that master data management will likely be one of the top considerations for the launch of an EIM program at St$.$ Rita's.

Please address the following questions:

What are the key takeaways from the vignettes in this chapter?

Why do you think the EIM team decided that master data management will be a top consideration $($priority$)$ for the launch of an EIM program at St$.$ Rita's?