This paper reports on our review of published research relating to how teams work together
to execute Big Data projects. Our findings suggest that there is no agreed upon standard for …

There is an increasing number of big data science projects aiming to create value for
organizations by improving decision making, streamlining costs or enhancing business …

How are data science systems made to work? It may seem that whether a system works is a
function of its technical design, but it is also accomplished through ongoing forms of …

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 …

The challenge in executing a data science project is more than just identifying the best
algorithm and tool set to use. Additional sociotechnical challenges include items such as …

Processes and practices used in data science projects have been reshaping especially over
the last decade. These are different from their software engineering counterparts. However …

Data Science projects aim to methodologically extract knowledge and value from data to
help organizations to improve performance. Dedicated process models are applied to …

Context: Big data has become the new buzzword in the information and communication
technology industry. Researchers and major corporations are looking into big data …

Through knowledge extraction from data with various methods, Data Science (DS) allows
organizations to achieve improvements in performance. The execution of these projects is …

This paper explores data science project management by first noting the need for a new
process management framework and then defines a process framework that effectively …