Data Structure for Visualization

Each row is one released hourly cell, grouped by every dimension listed below. The current UTC hour and cells below anonymous_min_cell_count are absent. The default threshold is 5 events and the allowed range is 2–1000.

Each row is one released daily goal cell. The view includes only anonymous events with an allowlisted goal retained in goal_event. The current UTC day and cells below anonymous_min_cell_count are absent. The default threshold is 5 goal occurrences and the allowed range is 2–1000.

Each row is one released daily cell by page group, referrer channel and device class. Grouping pages and dropping the hour and viewport releases far more of a low-traffic site's events than the hourly view. A cell is withheld below anonymous_min_cell_count, and also when the part of it the hourly view withholds would be smaller than that minimum, so comparing the two views never reveals a small count. Page groups are configured under Reporting → Page groups or as bi_page_groups in YAML.

The daily cells, with the ones too small to release rolled up into coarser rows instead of dropped: devices pooled first, then channels, then pages, then everything for the event and day. A pooled value is (other), meaning the part not shown in more detailed rows. Every row reaches anonymous_min_cell_count and follows the same rule as the daily view against the hourly view, and each event is in at most one row, so daily totals add up. The full-detail rows are exactly the daily view's rows.

How much of each completed day's anonymous traffic each event view releases, per website, as a band rather than a number, so a report can say how complete it is without revealing the day's total. Days with fewer events than anonymous_min_cell_count have no rows.

Each row is one released daily geography cell. The current UTC day and cells below anonymous_geo_min_cell_count are not shown individually; their counts may be released only in a qualifying other pool. The default threshold is 25 events and the allowed range is 10–1000.

Join declared metadata to reporting codes to display labels such as Tablet or Germany. These views contain configuration and built-in definitions, never observed traffic or counts. Administrators publish them with app:analytics:glossary:sync after migrations or metadata changes, or save through Reporting → BI glossary.

The six dimension views have one row per code in the deployment's default locale, with prefixed fields such as device_class_label and device_class_sort. Relate each one many-to-one to the matching fact column and display the label. For translated labels, filter bi_glossary_values_v1 to one dimension and one published locale before joining; joining all locales multiplies fact rows.

Use a left join and keep the original code when a label is missing: undeclared event names, deleted goals, and the synthetic country:other/continent:other pools have no dimension row.

SELECT f.event_day, f.goal_event,
       COALESCE(d.goal_event_label, f.goal_event) AS goal_label,
       f.event_count
FROM bi_anonymous_goals_v1 f
LEFT JOIN bi_dim_goal_event_v1 d ON d.goal_event = f.goal_event;

Administrators can define JSON properties and SQL column names in Data model, then regenerate these views for reporting on retained raw events:

• analytics_custom_events_v1: all event names in both privacy modes.
• analytics_custom_pageviews_v1: page views only.
• analytics_custom_goals_v1: events with a retained goal.

Modeled scalar properties become text columns, and numeric properties can also get a number column for calculations. Missing values, JSON null, arrays, and objects produce SQL null. These views expose individual rows without suppression and need separately approved raw-data access. They include raw rows already marked as archived while those rows remain retained; archive aggregate cells do not contain the custom properties.

The bi_anonymous_* views keep their existing dimensions and disclosure thresholds. Deleting raw events removes their custom properties from reporting, even when archived counts remain available.

• Configure event_hour as UTC; the physical timestamp may not carry a timezone marker.
• Connector-specific physical types vary; model event_day as a date and event_count as a whole number.
• Expect new hourly event data only after an hour completes, and goal and geography data only after a UTC day completes.
• Treat missing cells as withheld or unavailable, not as confirmed zero traffic.
• Remember that event_count counts event or goal occurrences, not visitors, unique people, or unique converters.
• Review stored BI extracts separately; later threshold changes do not remove earlier exports.