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Event-level data

As explained in Effective Data Analysis

Event-level data contains one record for each individual occurrence, such as a page view, click, or call.

Event-level data stores one raw record for each individual occurrence, such as a page view, click, or call. This granularity supports precise measurement, but its usefulness depends on available fields, timestamps, identifiers, and data quality. section 2.1.2

Inspect event-level data before selecting a method:

  • Check whether rows represent individual events or are already aggregated, such as one row per user per day. section 2.1.2
  • Verify shared primary keys, timestamp sources, action durations, action intervals, missing fields, and unavailable measures. section 2.1.2
  • Revise research questions when important measures are absent or available only in aggregate form. section 2.1.2

How Effective Data Analysis covers it

How deep it goes
Defines raw event-level structure and contrasts it with partial aggregation, then stops at dataset inspection rather than analysis.
Examples
Uses page views, clicks, and calls, with a sample page-view-events table as a concrete artifact.
What it assumes
Assumes a research question and enough domain context to inspect fields, timestamps, linkage, and missingness.
What you can do after
Evaluate whether a dataset supports precise questions by checking granularity, linkage, timestamps, missingness, and absent fields.
How it connects
Connects event-level data with data aggregation, primary keys, timestamps, missing data, and measurement selection.
Cover of Effective Data Analysis
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Related concepts

This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.