Thinking about data, business, and what comes next.
Practical questions about business analytics, data science, machine learning, AI and decision making. The focus isn’t technology for its own sake. It’s understanding problems, finding patterns, and asking better questions.
These notes are being written now. Each will be published here in full; until then, this is what each one will argue.
- 01
Business intelligenceComing soonWhat does a dashboard actually tell you?
A dashboard can show what happened. The harder question is what the information means, and what should happen next.
- 02
MethodComing soonFrom business question to data question
A strong analytical project starts by translating a business problem into questions the data can actually answer.
- 03
Predictive analyticsComing soonWhen should a business use predictive analytics?
Prediction is useful when it supports a decision. The first question isn’t which model to use, but whether a prediction would change what someone does.
- 04
Applied AIComing soonAI is not the starting point
Before asking what AI can do, ask what problem needs solving. Sometimes the answer is AI. Sometimes it’s better data, better reporting or a simpler workflow.
- 05
Data strategyComing soonWhat makes data useful?
More data doesn’t automatically create more insight. Useful data is data that helps answer a meaningful question or support a decision.
- 06
Data scienceComing soonWhy correlation matters in clustering
Clustering isn’t just about creating groups. The relationships between variables shape the structure of the data, and how those groups emerge.
