TY  - JOUR
T1  - Study of Data Steward Involvement in Agile Big Data Project Management
AU - El Desouky, Heba AU - Mazen, Sherif AU - Elramly, Mohamed 
JO  - International Business Management
VL  - 15
IS  - 6
SP  - 247
EP  - 255
PY  - 2021
DA  - 2001/08/19
SN  - 1993-5250
DO  - ibm.2021.247.255
UR  - https://makhillpublications.co/view-article.php?doi=ibm.2021.247.255
KW  - Agile
KW  -agile in big data
KW  -data steward
KW  -data governance project management
AB  - The area of big data is attracting the attention
of academia, industry and government across the world,
due to the rapid development of the internet, the Internet
of Things and cloud computing and the gigantic amounts
of data collected daily. However, the question, &ldquo;How to
set up and optimize a big data project for successful
assimilation of big data projects in organizations?&rdquo; is still
an open question. This is becoming an increasingly
challenging task that requires understanding the value of
big data, the challenges facing big data projects and the
steps involved in running a big data project. Many
researchers claim that failure rates for big data projects
are considerably high due to several aspects affecting
successful big data project management. In our study, we
investigate the unique aspects of planning and managing
big data projects. We propose an adaptation of traditional
roles in agile projects to accommodate the specific needs
of big data projects. Specifically, we propose and study
the involvement of data steward role in big data projects
to address the specific needs of such projects and
eliminate the causes of failure, thus, increasing the
successful completion rate of such projects. In this study.
We back our position with a case study of the application
of data steward in managing a big data project in a
company working in the meal delivery industry. Our
study lasted for a year and studied the performance of an
agile project team represented by team velocity and
productivity. Results show significant improvement.
ER  - 