Discover six key principles for effective data analysis, drawn from years of industry experience in consumer tech. These principles include establishing a baseline, normalizing metrics, applying MECE grouping, aggregating granular data, removing irrelevant data, and using the Pareto principle. These guidelines can help analysts uncover valuable business insights and improve their exploratory data analysis (EDA) practices.
Table of contents
Establish a BaselineNormalize the MetricsMECE GroupingAggregate Granular DataA Powerful EDA Tool: Group-By AggregationRemove Irrelevant DataApply the Pareto PrincipleSort: