You're racing against the clock on a GIS project. How do you decide which data discrepancies to tackle first?
When the clock's ticking on a GIS project, strategically addressing data discrepancies is crucial. Here's the best approach:
- Assess the impact. Prioritize errors that affect the largest dataset or the project's key outcomes.
- Check dependencies. Resolve issues in datasets that others rely on first to prevent downstream errors.
- Time vs. value. Focus on discrepancies you can fix quickly that will have a significant impact.
Which strategies do you find most effective when time is tight on a project?
You're racing against the clock on a GIS project. How do you decide which data discrepancies to tackle first?
When the clock's ticking on a GIS project, strategically addressing data discrepancies is crucial. Here's the best approach:
- Assess the impact. Prioritize errors that affect the largest dataset or the project's key outcomes.
- Check dependencies. Resolve issues in datasets that others rely on first to prevent downstream errors.
- Time vs. value. Focus on discrepancies you can fix quickly that will have a significant impact.
Which strategies do you find most effective when time is tight on a project?
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