Ask in Daasity
Use the AI assistant builtAsk in Daasity The in-app AI Analyst is a chat assistant built into into Daasity to ask questions about your data in plain English - answered from your own governed metrics.
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Use the AI assistant builtAsk in Daasity The in-app AI Analyst is a chat assistant built into into Daasity to ask questions about your data in plain English - answered from your own governed metrics.
The in-app AI Analyst is a chat assistant built into Daasity. Ask a question in plain language and it answers using your governed Daasity metrics - the same definitions behind your dashboards and Explores. No SQL, no report requests, no waiting on an analyst for a quick number.
Open AI Analyst from your Daasity workspace. You'll see "How can I help you today?" and a set of example questions. You can click one to run it, or type your own question in the box at the bottom.
Example starters include:
Top 10 products by revenue last 30 days
Revenue by channel last 90 days
Daily revenue trend this month
New vs. returning customers
Press Enter to submit, or Shift+Enter to add a new line. Ask in everyday language - you don't need to know table or field names.
As it works, AI Analyst shows what it's doing - finding the relevant fields, then running the query - so the process is transparent. The answer itself is written in plain English and typically includes:
A clear summary with the headline result called out (for example, the top product with its revenue and units), followed by a ranked breakdown.
A short insight interpreting the numbers - concentration, trends, or risks worth noticing.
Assumption and caveat notes flagged inline. For instance, if you ask for "last 30 days," it may note that it used the closest standard window (such as the latest 4-week period) and call out anything excluded. These notes are there so you can trust exactly what was measured.
View data. Click View data under any answer to expand the underlying rows behind the response.
Because answers come from your governed semantic layer, the numbers line up with the rest of Daasity.
Under an answer, open Dig deeper? for suggested follow-up questions tailored to what you just asked (for example, "Which retailers are driving this product's sales?"). Click one to run it, or simply type your own follow-up in the box - the assistant keeps the context of your conversation within the thread.
Each conversation is saved as a thread in the left panel under Recents, so you can return to a previous question or keep building on it. Start a fresh line of questioning any time with New thread, and use the search box to find an earlier conversation.
Name the time frame ("last 30 days," "this month," "Q2") - it removes ambiguity.
Name the dimension you care about ("by channel," "by product," "new vs. returning").
Straightforward data pulls are the sweet spot - a number, a ranking, or a trend comes back reliably.
Check the assumption notes on the answer so you know exactly what was measured.
For analysis or opinions, keep it open-ended and iterate. Ask follow-ups and sanity-check the result before you rely on it.
The workspace menu (click your workspace name, bottom-left) includes helpers that support your analysis:
Query History - revisit past queries.
Data Dictionary - browse the models, metrics, and fields available to ask about.
Domains - see the subject areas your questions can draw from.
Refresh Schema - pull in recent changes to your data model.
If you'd rather ask these same questions from Claude, Cursor, or another AI tool, connect it to your Daasity data with MCP.
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