Date of Award

9-1-2021

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Computer Science

First Advisor

John Talburt

Abstract

Data governance is mission critical. Organizations start to realize the data and information are very important assets. Data governance program could minimize the risk of data lose and maximize the data values. As existing best practices to implement data governance program, most of these practices rely on management strategies, which focus on data governance literacy education, enforcing data policy, standard and processes, etc. However, IT infrastructure strategy has not changed too much to support data governance achievement. Data governance requirements for system design usually is the last concern on the list. Most of the data governance programs collect metadata or metadata changes in a reactive way, which means to extract the metadata changes from system or service logs after the data operations are finished. The drawback for this kind of metadata collection is so obvious. Firstly, the system may not consider exporting the expected metadata information in the system log by design. Secondly, the latency and uncertainty for the system logs collection introduce more complexity in metadata collection and decrease the metadata quality. In order to implement data governance program more efficient, a solution must come from IT system design level. In this paper, a positive data control system which represents a well-implemented data governance system is defined. Essential components and operations for Positive Data Control (PDC) system has been laid out. PDC Data Access API, the core component of PDC, controls all the PDC system data in and out, which by design collects the metadata information about the controlled data operations automatically. We propose the design of PDC Data Access Layer. We also implement it against Hadoop distributed file system and HBase NoSQL database system.

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