Dataddo Data to AI

Report how current an entity's data is: when it was last written, how many rows, and the freshness policy the model declares, which says whether figures are current enough to act on.

Show an entity's selectable fields and its declared relationships to other entities. An entity modelled automatically can carry hundreds of fields, so the most-filled ones are returned by default and 'fields_selection' says how many were not — use 'matching' to search by name, 'fields' to name the ones you want, or 'offset' to page. A field not shown is not thereby absent. The field names here are the ones query accepts. Relationships listed here are the ONLY joins available — they are declared by the data model, never inferred.

Describe ONE flow in depth: how many rows carry a value per column, which are empty, which could identify a row, and the period the data covers. Use it after list_flows to judge whether a flow can answer a question before anyone models it. Reports MEASURED facts, not the schema's claims — a column can be declared and hold nothing. The most-filled columns are returned by default and 'columns_selection' says how many were not; use 'matching' to search by name or 'offset' to page.

List questions this data CANNOT answer, and why. A question listed here has no answer in this data; a nearby metric answers a different question. An empty inventory is not evidence there are no gaps: gaps are written by hand and derivation produces none.

List the business entities and blessed metrics in ONE model. Entities are business nouns (customer, invoice, deal), not source tables. This is what can be ASKED, which is narrower than what the account HAS — for that, use list_flows. declared_rows is what the PLATFORM says a flow holds, not a measurement. Returns a PAGE: 40 by default, at most 200, answerable first, with 'counts.entities_in_model' giving the true total — advance 'offset' rather than concluding the model ends there, and read 'counts.answerable_in_model' before judging from one page how much can be queried. A page can come back SHORTER than you asked when the response budget trims it; 'entities_truncated' says so, and you then advance by the number you RECEIVED, never by the limit you requested. Metrics are listed once, on the first page, and are model-wide.

Answers "what business data do we have", "what are we connected to" and "what systems feed this account": lists the Dataddo FLOWS this account is connected to and which ones a model covers, so they can actually be queried. Each flow reports how many columns it has, not the columns themselves — call describe_flow for one flow's inventory. Check columns_from: source_row_count and source_column_count describe the SOURCE behind a flow and are upper bounds, because a flow may filter rows or emit fewer columns. What those columns MEAN still requires a model: a flow with queryable=false is connected and inspectable, not answerable; list_entities has what can be asked. Returns a page: 20 by default, at most 200, with counts.matched_filter giving the true total — advance 'offset' rather than concluding the account ends there. A page can come back SHORTER than you asked when the response budget trims it; 'flows_truncated' says so, and you then advance by the number you RECEIVED, never by the limit you requested.

List the semantic models available — each covers one source system and contains MANY entities — and which is the default. (A model here is a whole semantic layer, not a single table as in dbt.) Use it when you are about to ASK something and need to know which world to ask in. Models cover only the part of the account that has been modelled; what the account is connected to is list_flows.

Query an entity. Select fields by name and traverse relationships with dots (e.g. 'account_manager.full_name'); filters, grouping and ordering use the same names. Blessed metrics encode which of several defensible definitions (of revenue, say) the business uses. A metric answers what the business means; an aggregate answers exactly what was asked and nothing more. describe_entity gives this entity's fields and how to write filters against them. Set dry_run to compile and return the SQL without executing it. This tool does not accept SQL.

Check whether refreshing an entity would return fresher data. It changes nothing: flow-backed answers are already refetched whenever the platform's version of the flow moves, and this server never makes the platform re-extract from the source system.

Record that an ANSWER was wrong: a figure a person says is off or contradicts what they know. Not for refusals or errors, which are already logged. Returns what is known about the entity — unreviewed fields, what its flow is scoped to — which is often the explanation of a wrong figure.

Show the most common values of a field, with counts: how the source system spells them. = and in match exact spellings, so a guessed value that is spelled differently matches nothing, without an error.

Find entities, fields, relationships and metrics by keyword across a model (or all models). Faster than calling describe_entity repeatedly when you are looking for 'the overdue one' or 'whatever holds revenue'.