Stable Panther

Data science isn’t about fancy algorithms. It’s about asking the right questions and finding answers in your data.

Start with the business problem

What decision are you trying to make? What information do you need? The algorithm comes last. Most “data science” projects fail because they start with the data, not the question.

Clean data beats clever models

Spend 80% of your time on data cleaning and validation. A simple model on clean data beats a complex model on messy data every time.

Visualize first, model second

Before you build anything, look at your data. Scatter plots, histograms, correlation matrices. The patterns you need might be obvious.

Start simple

Linear regression. Decision trees. These work for most problems. Don’t reach for deep learning until you’ve tried the basics.

Measure what matters

Accuracy is nice, but what about precision? Recall? Business impact? Pick metrics that actually matter for your use case.

Document everything

Your future self won’t remember why you made that transformation. Document your assumptions, your process, and your reasoning.

Need help making sense of your data? Get in touch and let’s discuss your analytics challenges.