Nine Questions to Evaluate a Data Science Team's Process: Exploring a Big Data Science Team Process Evaluation Framework Via a Delphi Study

Nine Questions to Evaluate a Data Science Team's Process: Exploring a Big Data Science Team Process Evaluation Framework Via a Delphi Study

Life cycle

Human resource management

Petroleum reservoir evaluation

Project management

Data Science

While the lack of an effective team process is often noted as one of the key drivers for data science project inefficiencies and failures, there has been minimal research on how to evaluate a data science team's process. Without an evaluation framework, it is difficult for data science teams to understand their team process strengths and weaknesses. To help address this challenge, this exploratory research, via a Delpha study, identified nine key questions a data science team could answer to help evaluate their process. In short, the study identified questions evaluating the team's communication (within the team and with stakeholders). The study also identified team process questions (e.g., the use of iterations, life cycles and a prioritization process for potential tasks). Future research could explore how data science teams can best improve their process by leveraging and refining these questions as well as defining an overall data science project management evaluation framework. 2022 IEEE.

2667-2672

Saltz, Jeffrey

2022 IEEE International Conference on Big Data, Big Data 2022, December 17, 2022 - December 20, 2022

2022

conferencePaper

10.1109/BigData55660.2022.10020499

http://dx.doi.org/10.1109/BigData55660.2022.10020499