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Factors in the Institution That Impact the Success of Big Data Science Projects
Note: This survey is anonymous. No personal identifying information is collected. Participation is voluntary. Please answer all questions in relation to your work on Big Data Science projects.
SECTION I – DEMOGRAPHIC INFORMATION
1.
Age range
22–31
32–41
42–51
52–61
62+
2.
Gender
Male
Female
Non-binary
Prefer not to answer
Prefer to self-describe
3.
Years of experience working on Big Data Science projects
1–5 years
6–10 years
11–15 years
16–20 years
21+ years
4.
Approximate size of your organization (all employees)
1–50
51–500
501–5,000
5,001+
SECTION II – CULTURAL FACTORS
5.
I am aware of how cultural differences among team members can affect Big Data Science project work.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
6.
I adjust my communication style when working with culturally diverse colleagues on Big Data Science projects.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
7.
I feel comfortable collaborating with colleagues from different cultural backgrounds on Big Data Science projects.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
8.
My organization encourages cultural awareness and inclusion in Big Data Science project teams.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
SECTION III – TECHNOLOGY READINESS AND CHANGE
9.
I keep up with new tools, methods, and technologies relevant to Big Data Science.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
10.
My organization provides adequate training to help employees adopt new Big Data technologies.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
11.
Technology support (for example, help desk or engineering support) is available when I encounter issues in Big Data projects.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
12.
Overall, new Big Data technologies improve the quality and effectiveness of our project outcomes.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
SECTION IV – RESOURCE ALLOCATION
13.
My organization provides sufficiently skilled staff to deliver Big Data Science projects successfully.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
14.
The technical infrastructure (for example, compute, storage, data platforms) is adequate for our Big Data Science projects.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
15.
Project budgets for Big Data Science initiatives are sufficient to meet project objectives.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
SECTION V – PROJECT SUCCESS
16.
The most recent Big Data Science project I worked on was completed on time according to the established schedule.
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
Strongly Disagree
Disagree
Neutral
Agree
Strongly Agree
17.
Stakeholders were satisfied with the final outcomes and deliverables of the most recent Big Data Science project I worked on.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
18.
Overall, the most recent Big Data Science project I worked on was considered successful by key stakeholders.
Strongly disagree
Disagree
Neutral
Agree
Strongly agree
Strongly disagree
Disagree
Neutral
Agree
Strongly agree