A Method of Evaluation and Prioritization of Data Governance Activities in Big Data Projects

The Framework described aims to provide the proposed structure and outline of content for organizing the evaluation of Data Governance for business intelligence and business analytics projects belonging to the data department. In order to ensure the framework is an accurate reflection of the work done in a company, it is essential to gain community consensus for the Framework which hopefully will become the basis for future work, studies, and applications. The document provides a description of the work and the methodologies in order to understand better the use of the framework, however, it is important to note that these steps are presented in a linear way but to build the non linear methodologies were occupied like Crisp-DB in order to have a continued and continuous feedback with the stakeholders. Hopefully, the Guide will continue improving itself (considering that the world related to big data is in continuous changing). In order to evaluate and validate the framework we conducted a test but we hope that future works will cover a bigger amount of data doing some extensive tests in order to validate it also from a statistical point of view. This edition is more concerned with outlining the structure of Data Governance also giving a framework and testing. This text will deal with presenting a framework for evaluating the implementation of the Data Governance program in each individual company project. Specifically, the implementation of this program in business intelligence and business analytics projects belonging to a big data department will be evaluated. A set of activities has been identified, which each project should implement , which are of fundamental importance from the perspective of Data Governance. The execution of these activities will be evaluated using an evaluation framework. The evaluation will be a process of cooperation between the team responsible for the project and the Data Governance team and will consist of a calculation of the completion percentage. The percentage of completion will take into consideration the quality metrics recognized for assessing the quality of the data. Subsequently, the framework proposes a support phase by the Data Governance team to the team responsible for the project. In this support phase, prioritization advice will be provided on the activities to be carried out based on a qualitative/quantitative model that takes into consideration the percentage of completion and the impact that each activity has in the business. This work supports the hypothesis that Lean Thinking, Process, Portfolio, Program and Project Management, and the Work System Theory, can complement the models and standards of Governance and Management of Enterprise IT, with an approach not existing in these models and standards of Enterprise IT, and suggests a Lean Framework that can support Governance and Management of Enterprise IT.