Comparing Data Science Project Management Methodologies

Assignment Title: Comparing Data
Science Project Management
Methodologies
Name:
Student Id:
Student Name: Student Id: 1

Contents
Introduction............................................................................................................... 3
Data science process.................................................................................................... 3
A need for an improved methodology............................................................................... 3
Methodology............................................................................................................. 4
1. Scrum Agile Method.......................................................................................... 4
2. Agile Kanban................................................................................................... 4
3. CRIP-DM........................................................................................................ 5
4. Baseline.......................................................................................................... 6
Findings................................................................................................................... 6
Conclusion................................................................................................................ 6
References................................................................................................................ 7
Student Name: Student Id: 2

Introduction
Data science is an upcoming field that combines many domains including data management,
software development and statistics. [9] Due to increasing data collection abilities,
availability of storage of data and advancing data analysis technology, the field of data
science is growing rapidly. There has raised a need to research on the best methodology that
will enable effective communication and coordination in a data science projects. Due to this
demand, I choose to do a research on various methodologies that can be applied in data
science. Application of a good method will benefit the data science team in a great way.
Some of these benefits are selection of good data architecture, identifying good analytical
techniques and selection of the member to be included in the team.
This research paper I intend to discuss four methodologies that can be applied in the data
science project. These methodologies are Agile Scrum, Agile Kanban, CRIP-DM and a
baseline. I will also compare these methodologies by use of a controlled experiment and
know which methodology is better. Lastly I will conclude on which methodology is best for
data science projects.
Data science process
Data science process is the process of acquiring, extraction of data, data combination, data
modelling, data analysis, report interpretation and drawing inferences. [1] Earlier before the
software development process was thought as an individual process. A classic phased
development was defined and the each phase was had a series of tasks. Due to the rapid
growth of technology there was a need to come up with a methodology that will allow a team
to coordinate in development process.
A need for an improved methodology
Those who work in the data science solve problem through analysis of data and answer
question by interpreting the reports. There is a need of an improved methodology that will
help the group to focus on task coordination, process and the technology. Due to lack of an
improved methodology a research shows that 55% of data science projects do not complete
and some fall out of objectives. As there is many reasons as to why data science projects are
Student Name: Student Id: 3