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#01How to use Gatlas

Views in 3 minutes

Feature3 min read

Have you ever found yourself checking the same data or rebuilding the same analysis over and over? Views help you turn raw source data into reusable business datasets, so Claude can answer recurring questions without reconstructing the logic every time.

What is a view?

Definition: view
A view is a reusable business dataset with consistent transformation logic, context and definitions. It converts raw data from systems such as Stripe, Shopify or your accounting platform into a structure designed around a business question.

For example, instead of repeatedly joining transactions and customer records, you can create one customer view containing customer names, countries, regions and revenue. Claude can then reuse that view across future analyses, reports and dashboards.

Twenty raw transactions on the left become a curated view on the right: totals for revenue, salaries, logistics, purchases, software and marketing, and a net result of +21,530.
Example data. Raw transactions become business areas and one net result, defined once and reused by every question after.

How to create a view

You do not need to write SQL or manually map every field. Describe the result you want, and Claude can explore the data available through Gatlas, propose the transformation and create the view.

You need Claude connected to Gatlas through a Read/write MCP connection. A Read-only connection can explore data but cannot create a view. See Using your MCP connection.

  1. Explore the available data

    Start by asking what information is available in your connected source. This allows Claude to inspect the relevant tables and fields before deciding how the view should be structured.

    Prompt
    What customer-related data is available in my raw data from Stripe?

    Claude will explain what customer, transaction and revenue information is available, including any limitations that could affect the analysis.

    Claude lists the Stripe customer data available for Test company, such as customers, charges and invoices, with the customer fields in each, and notes that they all link through the customer ID.
    Available Stripe customer data.

  2. Request the transformation

    Describe the business result you need using familiar business language. Include the dimensions and metrics you expect, but let Gatlas map them to the actual source fields.

    Prompt
    Create a customer view grouped by country and geographic region. Include customer name, revenue, country and region.

    Before creating the view, review the proposed fields and definitions. Check how customers are identified, how revenue is calculated and how countries are assigned to regions. This ensures the view reflects the intended business meaning.

    Claude asks how to define revenue, region and row grain, then publishes the view Test Company Customer Revenue by Country and Region, with one row per customer.
    Proposed customer view.

  3. Use the result

    Once created, the view becomes a documented dataset that Claude can query directly. You can use it for one-off questions, recurring analysis, reports or dashboards without rebuilding the transformation.

    Try it
    Show revenue by country, including the number of customers and geographic region, using the new customer view.

    Because the business logic already exists in the view, Claude can focus on answering the question rather than rediscovering the underlying data structure.

    Using the new view, Claude returns revenue by country with region and customer count, led by Norway at 168,905 euros from 14 customers.
    Revenue by country result.

Why this matters

Views create a shared and reusable definition of important business concepts such as customers, revenue, products or P&L. Future analyses can be faster, more consistent and easier to verify because they all start from the same documented logic.