Data Analytics, Data Science
A tutorial on connections, coincidences, curiosity, and contradictions as strategies to explain insights from data.
Explaining why something happens in your data is not easy. You may even find something exceptional in your data, but after your discovery, you must explain why this event occurred. In this article, I’ll show four possible strategies to explain your insights. I have not invented these strategies, they derive from a book I recently read, by Gary Klein: Seeing What Others Don’t: The Remarkable Ways We Gain Insights.
Before diving into the proposed strategy, I will briefly illustrate the basic steps to extract insights from data.
Follow the steps described below to extract an insight:
- Identify Key Data — After data collection, identify the most critical information to analyze. For instance, negative reviews and high return rates.
- Explore the Key Data — Plot and examine the data for patterns or trends. For example, do negative reviews spike when return rates are high?
- Extract Insights — Formulate hypotheses about your data and apply statistical or data analysis tools to…