Quickstart

Mora is an AI-powered analytics workspace that connects to your data warehouse, lets you write and transform SQL, and turns the results into shareable dashboards. This guide walks you through everything from your first datasource to a fully populated team workspace. Work through the sections in order:

• Initial setup: Connect a datasource, write your first query, and try the AI assistant. ~10 minutes
• Personalize your workspace: Sync app data, generate datasource knowledge, invite teammates, and build a dashboard. ~25 minutes
• Make Mora your team’s data analyst: Migrate dashboards, shape data with no-code transformations, and operationalize sharing. ~1 hour

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Initial setup

Time required: ~10 minutes. Mirrors the Get started checklist in the bottom-left of the sidebar. After signing up, you’ll be taken through a short onboarding flow that collects your profile, sets up your workspace, and starts a 14-day Pro trial. Once that’s done, you’ll land in the app and can pick up here.

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1. Connect your first datasource

A datasource is a direct connection to your SQL database or warehouse. Mora supports seven types out of the box.

1. Open Settings → Datasources and click Add datasource.
2. Pick the type and give the datasource a name.
3. Fill in the credentials (see the cheat sheet below).
4. Click Test connection to verify Mora can reach your database.
5. Click Add datasource.

Mora will sync your catalog (schemas, tables, columns) in the background. The catalog powers SQL autocomplete and helps the AI find the right tables. See Datasources for per-database setup guides and troubleshooting.

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2. Write your first dataset

A dataset is a saved SQL query tied to a datasource. Datasets are the foundation of every chart on every dashboard.

1. In the sidebar, expand Datasets and click the + button (or use the empty-state Create a dataset card).
2. Pick the datasource you just connected.
3. Write a query in the SQL editor, try something simple to start:
   SELECT date, COUNT(*) AS total_orders
   FROM orders
   GROUP BY date
   ORDER BY date DESC
   LIMIT 100
   
4. Click Run (or press Cmd+Enter) to preview results in the bottom pane.
5. Click Save in the top-right (or press Cmd+S) to save and publish.

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3. Try the AI assistant

The AI assistant lives in the right-hand chat panel. It can write SQL, debug queries, build charts, manage dashboards, and answer questions about your data.

1. On the home page, a dataset page, or a dashboard page, press Cmd+/ (or click the right-pane toggle in the header).
2. Pick a mode at the bottom of the panel:
   • Auto: the AI decides which tools to use. Best default.
   • SQL: focused on SQL editing and schema exploration.
   • Dashboard: focused on dashboard, chart, and filter management.
   • Ask: read-only. The AI can answer and run queries, but cannot create, update, or delete anything.
3. Type a question, for example:

   “Show me a line chart of total orders by date for the last 90 days.”

The AI will draft SQL, run it, and offer to apply changes you can accept or reject inline.

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Personalize your workspace

Time required: ~25 minutes. These steps round out the in-app Get started checklist and make the workspace feel like home.

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Sync data from third-party apps

Connections sync data from apps like Stripe, HubSpot, and Salesforce into a schema inside one of your existing datasources. Once synced, the data shows up in your catalog and can be queried like any other table.

1. Open Settings → Connections and click Add connection.
2. Search for the app or pick one from the popular list.
3. Choose the destination datasource the data will sync into. (If you haven’t connected a warehouse yet, do that first in Settings → Datasources.)
4. Authenticate or paste an API key, depending on the connector.
5. Pick a target schema (e.g. stripe, hubspot).

Connections currently available: See Connections for detailed per-app setup guides. For connectors not listed here, browse the full catalog at mora.com/integrations.

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Generate datasource knowledge

Mora can read your catalog and write a narrative description of what each schema and table represents. This knowledge is fed into the AI assistant so it picks the right tables for your questions.

1. Open Settings → Datasources and click into a datasource.
2. Find the Knowledge section and click Explore.
3. Mora’s agent inspects the catalog and generates a knowledge document. You can edit or extend it later.

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Invite your teammates

1. Open Settings → Members.
2. Enter a teammate’s email and click Invite.

New invitees land at the member role. Once they accept, you can promote them to admin or owner from the role dropdown next to their name.

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Build your first dashboard

A dashboard (sidebar label: Dashboards) is a grid of charts. Each chart is linked to a dataset.

1. In the sidebar, expand Dashboards and click the + button.
2. Click Add block in the top toolbar, an empty Table block appears on the grid.
3. Click the block to open the side pane:
   • Data tab, pick a dataset.
   • Visualization tab, choose Table, Graph (line, area, bar, scatter, or pie), or Stats. Configure axes, columns, and aggregations.
4. Drag the block to reposition; resize from the corners.
5. Click Add block again to layer in more charts.

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Add dashboard-level filters

Dashboard filters apply to every chart on the dashboard at once, useful for date ranges, customer segments, or any column shared across datasets.

1. On a dashboard, click the Filters button in the top toolbar.
2. Pick the columns to filter on (Mora finds shared columns across the datasets in use).
3. Set a value, pills appear in the toolbar that you can drag to reorder.

See Dashboard filters for the full reference.

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Make Mora your team’s data analyst

Time required: ~1 hour. Do this when you’re ready to migrate from your existing analytics tools and roll Mora out across the team.

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Migrate dashboards from your previous analytics tool

Mora doesn’t import dashboards directly, but the AI makes recreation fast.

1. Copy the SQL from your existing tool (Looker, Metabase, Mode, Hex, etc.).
2. Open a new dataset in Mora, paste the SQL, and ask the AI: “Convert this Looker SQL to Snowflake dialect.”
3. Run the query, save the dataset.
4. Add the dataset as a block on a dashboard and configure the visualization to match the original.

Repeat per chart. The AI keeps the context of your schema, so dialect translation and column naming are usually one-shot.

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Shape your data with no-code transformations

Transformations are a click-and-drag layer that runs on top of your saved dataset results, no SQL rewriting required.

• Group rows by one or more columns.
• Aggregate with sum, average, count, median, min, max, percentage, and more.
• Filter with equals, contains, ranges, relative dates, booleans, IN, etc.
• Sort by any column.
• Hide columns from the visualization without removing them from the underlying data.

Each chart has its own transformation configuration on top of the dataset’s, so the same dataset can power multiple charts with completely different shapes.

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Share, favorite, and duplicate

• Datasets: toggle from Draft (private) to shared via the dataset overflow menu. Shared datasets show up under the Datasets section in everyone’s sidebar.
• Dashboards: favorite from the dashboard header to keep them at the top of your sidebar; duplicate to fork a copy you can edit independently.

See Sharing dashboards and Duplicating dashboards.

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Org admin essentials

• Roles: promote teammates to admin or owner from Settings → Members.
• Billing: the Billing item in the settings sidebar (visible to owners and admins) opens the Stripe Customer Portal in a new tab. Manage payment methods, change plans, view invoices, and cancel from there.
• Datasource credentials: rotate or update from Settings → Datasources → [datasource].

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Power features

A few shortcuts and tools that pay off after the first day. Quick navigation: press these in sequence (not held):

• G then H: home
• G then B: pick a dashboard
• G then D: pick a dataset
• G then O: pick a datasource
• G then S: settings

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Common chat prompts

The AI is most useful when it’s part of your daily routine. A few categories of prompts to get you started:

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Finding data

• “Which tables have user-level events?”
• “Show me the schema of the orders table.”
• “Are there any tables with revenue data?”
• “Find columns related to customer_id across the catalog.”

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Building charts

• “Plot weekly signups as a line chart.”
• “Add a stats block for total ARR with a week-over-week delta.”
• “Create a bar chart of revenue grouped by plan, sorted descending.”
• “Build a dashboard with the three most useful charts for tracking activation.”

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Writing & fixing SQL

• “Optimize this query.”
• “Why is this query failing?” (Or click Fix with AI when the editor surfaces an error.)
• “Convert this Looker SQL to Snowflake dialect.”
• “Add a 30-day rolling average to this query.”

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Reporting & summaries

• “Summarize this dashboard for our weekly review.”
• “What changed week over week on this dashboard?”
• “Which metrics on this dashboard look unusual right now?”

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Getting help

If you get stuck, we’re happy to help.

• In-app AI: open the chat (Cmd+/) and ask. The assistant can answer most questions about your workspace, your data, and how to use Mora.
• Email: support@mora.com.