Zansa › Answers › Forecasting and data science
How do I get started with data science if my data is messy and scattered?
Start by choosing one valuable decision, list the data it needs, and consolidate that data into one place with clear definitions. Fix the most important quality issues, build a simple dashboard to establish trust in the numbers, then try a baseline forecast. Only then consider machine learning.
A step-by-step path:
- Pick one use case, such as weekly stock ordering.
- Identify sources and who owns them.
- Export or connect data into a central store.
- Reconcile totals to finance records.
- Document definitions.
- Report, then forecast.
Progress in small, finished steps beats a large plan that stalls. A structured review, like Zansa's fixed-fee Data Health Check, is one way to find what is usable before committing to a larger build.
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