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Why Most Data Projects Fail & How to Avoid It • Jesse Anderson • GOTO 2023
Explore the common pitfalls that lead to failed data projects and learn how to avoid them by implementing successful strategies for data science and engineering.
- 85% of data projects fail
- Wrong ratio of data scientists to data engineers (1:1 instead of 5:1)
- Importance of clear goals and definition of success
- Need for people with specialized skills
- Importance of organization and communication
- Organizational change required
- Avoid blindly following vendors
- Need for accountability and measurable return on investment (ROI)
- Data projects require plan and execution
- Success is correlated with having the right people and definitions
- Care should be taken when selecting data engineers
- Multiple teams and skills required for success
- Value creation is a people change, not just a technical one