Data Engineering is 80%+ of most AI projects, so building a good Data Engineering Environment is key to AI Project Success. As the manager of this project, you need to make sure you have correct staffing needs. What's the most critical role to staff for in the Big Data / Data Engineering Environment?

CPMAI notes that over 80 % of AI effort is spent in data engineering—ingesting, cleaning, transforming, and pipelining data. Therefore, the data engineering role is the single most critical position to staff for a robust big-data/AI environment.

A – Data scientists depend on well-engineered data; they are ineffective without it. B – Including scientists is useful, but data engineering remains the bottleneck. C – Senior management is vital for governance, not day-to-day pipelines. E – All roles help, yet data engineering is disproportionately essential per CPMAI.

1. Cognilytica. “CPMAI v7 Methodology Guide,” Appendix B, pp. 92-93 (AI Project Roles; 80 % data engineering statistic).

2. Cognilytica. “CPMAI v7 Methodology Guide,” Sec. 1.4, p. 18 (Importance of Data Engineering to AI Success).