College for Professional Studies
MS Information Technology Management
School of Computer & Information Science
Thesis - Open Access
Number of Pages
Data is collected from a number of entities within the business environment; it is the essential component that guides the decision making process. Data management is a topic that continues to be discussed as our ability to collect and store data expands. The purpose of this study was to determine whether the data, in the context of the enterprise and its management, was understood allowing best practice data collection and storage policies to be defined. Data collection and storage are tightly coupled in the discussion of storage growth. The literature review showed that a number of data management lifecycles and solutions exist that support storage management policies, but do not focus upon controlling storage growth. Policies that affect or control storage growth do not necessarily reside within the application. This study deployed a survey that collected data which defined the problem area within the business enterprise. The survey data revealed that management does not understand the cost of storage nor data value. Furthermore, it was determined that the preferred method within the enterprise to handle the growing data was to expand storage. In addition to the survey, two interviews were used to substantiate the findings making the study a mixed method approach. The scope of the study was to define or provide a method to define best practice policies that would reduce or control storage growth. The findings have led to the development of the storage quadrant framework that provides the enterprise a method to define best practice policies.
Date of Award
© Anthony Daubenmerkl
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Daubenmerkl, Anthony, "Understanding Data Within The Enterprise To Control Or Reduce Data Storage Growth" (2011). All Regis University Theses. 738.