Explorar dados

Choose the source, tick the columns you are interested in and, if you want a total per group, choose the dimension and the calculation (sum, average, median, max, min, count). Without grouping, the table comes out detailed, row by row.

Answer a passing question without building a dashboard: choose the dataset, tick the columns, group by a dimension and choose the calculation (sum, average, count...). It is the same engine as the dashboards — with the same values governance and the same scoping by company. — this is the role of the "Explore data" screen within the platform.

Without grouping, the screen returns the detailed rows of the columns you ticked. When you choose a dimension in "Group by", the FUNCTION (sum, average, count…) starts to apply to the numeric columns — those marked with (Σ) — and each row of the result becomes a group. Change the function without rebuilding anything: the same slice answers "how much it adds up to" and "how many there are" with two clicks on Run.

Datasets of tables with company fields bring those fields as columns (cc_) to tick, filter and export, and in "Group by" to count and sum per field value (a record from another table shows by its name). Sensitive ones show only with "See Values"; without it, grouping by them becomes a single group, •••.

Explorer has no query of its own: it calls exactly the same execution as the dashboards. Anyone who cannot see values still sees the mask, and the scope of the company in use is built into the source. Exploring opens no door that the dashboard does not open.

When the set exceeds the row limit that the screen returns, a truncated-result warning appears above the table — what you see is a portion, not the total. In that case, narrow the question: group by a dimension (the aggregate almost never truncates) or choose a more tightly scoped dataset. The table pages from 10 to 500 rows per page, and the CSV button exports what is rendered on the screen.

If the administrator created a row rule for the dataset (for example, "unit = yours"), Explorer applies the rule before any filter of yours. You cannot see it or remove it — it is part of the scope, like the company. The result is the same as the dashboard would show.

Explorer is for the passing question — it does not save. When the slice deserves to become ongoing monitoring, build a component in the dashboard builder with the same dataset and the same grouping: then it gets a period, a global filter, a color rule and a fixed place.

"What do the receivables add up to by nature? And by customer? — without building a dashboard" — when that question comes up, this is the screen that answers it.