Data analysis turns relevant business data into conclusions that support decisions. A chart is not the goal by itself: a simple cost breakdown can save money, while an elaborate market analysis can fail if it misses what customers think. Start with the decision you need to inform, not the most impressive tool available. section 1.2.1
The workflow changes with the question and the data, but its basic steps are:
- Collect and clean relevant input data. section 1.2.1
- Process the data with suitable analytical methods. section 1.2.1
- Present conclusions to the intended audience. section 1.2.1
A restaurant’s menu decisions
Compare frequently ordered dishes with rarely ordered ones. Across a chain, examine popularity by location and time of day. These descriptions can inform stock management, staffing, and promotions; they do not automatically dictate a single correct action. section 3.3
Descriptive statistics and visualizations help reveal patterns, relationships, and anomalies before more advanced analysis. Generative AI can suggest methods or code, but it is a supplement to an analyst, not a substitute for checking calculations, testing code, and applying domain knowledge. More data or a polished answer is not necessarily a useful insight. section 3.3 section 1.2.3 section 1.2
