Data Science is an emerging field with a significant research focus on improving the techniques available to analyze data. However, there has been much less focus on how people should work together on a data science project. In this paper, we report on the results of an experiment comparing four different methodologies to manage and coordinate a data science project. We first introduce a model to compare different project management methodologies and then report on the results of our experiment. The results from our experiment demonstrate that there are significant differences based on the methodology used, with an Agile Kanban methodology being the most effective and surprisingly, an Agile Scrum methodology being the least effective
Data science projects have unique risks, such as potential bias in predictive models, that can negat...
The goal of Data Science projects is to extract knowledge and insights from collected data. The focu...
The appearance of Agile methods has been the most noticeable change to software process thinking in ...
Data Science is an emerging field with a significant research focus on improving the techniques avai...
This paper explores the factors that impact the adoption of a process methodology for managing and c...
This paper reports on a controlled experiment comparing different approaches on how to guide student...
Data science projects have become commonplace over the last decade. During this time, the practices ...
The lack of effective team process is often noted as one of the key drivers of data science project ...
Processes and practices used in data science projects have been reshaping especially over the last d...
This paper first explores the concept of a lean project and defines four principles team should foll...
Developments in big data have led to an increase in data analytics projects conducted by organizatio...
Information Science is an arising field with a huge exploration centre around improving the methods ...
The amount of data generated by organizations and systems is growing exponentially. At the same time...
Majority of the IT companies realized that ability to analyse and use data, could be one of the key ...
Agile methods, initially used by cross-functional teams in software development projects, can also f...
Data science projects have unique risks, such as potential bias in predictive models, that can negat...
The goal of Data Science projects is to extract knowledge and insights from collected data. The focu...
The appearance of Agile methods has been the most noticeable change to software process thinking in ...
Data Science is an emerging field with a significant research focus on improving the techniques avai...
This paper explores the factors that impact the adoption of a process methodology for managing and c...
This paper reports on a controlled experiment comparing different approaches on how to guide student...
Data science projects have become commonplace over the last decade. During this time, the practices ...
The lack of effective team process is often noted as one of the key drivers of data science project ...
Processes and practices used in data science projects have been reshaping especially over the last d...
This paper first explores the concept of a lean project and defines four principles team should foll...
Developments in big data have led to an increase in data analytics projects conducted by organizatio...
Information Science is an arising field with a huge exploration centre around improving the methods ...
The amount of data generated by organizations and systems is growing exponentially. At the same time...
Majority of the IT companies realized that ability to analyse and use data, could be one of the key ...
Agile methods, initially used by cross-functional teams in software development projects, can also f...
Data science projects have unique risks, such as potential bias in predictive models, that can negat...
The goal of Data Science projects is to extract knowledge and insights from collected data. The focu...
The appearance of Agile methods has been the most noticeable change to software process thinking in ...