> ## Documentation Index
> Fetch the complete documentation index at: https://docs.generalvalidation.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Getting started

> Start your free trial, connect your Azure execution environment, and reconcile your first source and target datasets.

General Validation reconciles source and target data so you can verify that a
pipeline or migration produced the expected outcome. You use the hosted
application to discover datasets, define checks, and review runs. Validation
executes in your Azure subscription.

Configuration, schemas, run status, verdicts, counts, and artifact references
are stored by General Validation. Source and target rows, credentials, staging,
exact result values, and captured failed rows stay in your Azure environment.
Your browser reads exact results directly from your customer-owned storage.
See [Security and the data boundary](/security-and-data-boundary).

## Before you start

Have these ready:

* A Microsoft work account in the Entra directory your organization will use.
* An Azure subscription in that directory and an administrator with **Owner**
  rights who can deploy the execution environment.
* A supported source and target dataset that should reconcile. Start with one
  well-understood pair and a row-count check.
* Access to a directory administrator if your tenant requires admin consent.

Supported inputs include qualified flat Parquet and Delta datasets, exact-file
CSV, Azure SQL Database tables, and supported Fabric Lakehouse and Warehouse
tables. Review [Supported scope](/supported-scope) for the format,
schema, and access requirements.

## 1. Start your trial

Open [General Validation](https://app.generalvalidation.com) and choose
**Sign in with Microsoft**. Use your work account.

For a new organization, enter the name your team should see and choose
**Start 7-day trial**. This connects your Entra directory, makes you the first
organization Owner, and starts the trial immediately. No credit card is
required.

The trial includes five active Dataset Pairs and ten Pairs created in total,
including archived or deleted Pairs. See
[Trial and billing](/licensing-and-activation).

If your directory already has an organization, ask an Owner to invite your
work account. Sign in and choose **Accept invitation**. Invitations do not
send an email automatically.

## 2. Connect your execution environment

Open **Environment** and enter an environment name, subscription ID, and Azure
region. Optionally enter an Entra group ID for colleagues who need to read
exact results and failed-row artifacts in the browser.

Choose **Continue to setup**. If the page shows **Admin consent needed**, a
directory administrator completes the consent step, then an organization Owner
chooses **Retry preparation**.

Review the resources and permissions, choose **Deploy to Azure**, and complete
the deployment in Azure. Return to General Validation and choose **I've
deployed it, verify and finish**. Continue once the environment is ready.

[Set up your Azure environment](/installing-general-validation) walks
through the complete process. Azure resource consumption is billed to your
subscription, including during the free trial.

## 3. Discover and prepare your datasets

In **Discovery**, register an Azure Data Factory or Microsoft Fabric workspace.
The discovery source identifies the metadata to browse; the separate execution
factory runs your checks.

For Fabric, follow [Connect Microsoft Fabric](/connect-microsoft-fabric) to
review workspace access and complete the guided connection. Discovery and
table-access checks run through your customer execution factory.

Select the source and target datasets in the catalog and choose **Import
selected**, or use **Import & prepare** for an individual item. Import starts
schema and source-access preparation automatically.

Wait for both datasets to become ready. If preparation needs attention, open
the Dataset and follow its specific remediation. Catalog visibility alone does
not mean a dataset can run.

## 4. Create a Pair and a Test

Create a Dataset Pair from your prepared source and target. Confirm the
selection before saving: a Pair's source and target cannot be changed later.

Add a row-count Test first. Set the comparison and tolerance to match what you
expect from this pipeline. Add aggregates or keyed value checks after that
first control works. Follow
[Create your first Test](/creating-your-first-test) for the authoring
steps and supported check types.

## 5. Run and review

Run the Test and open its result. The run first executes in your customer Data
Factory, then delivers the result metadata. Review the final verdict and any
reported error after delivery completes.

When you open a delivered result, exact comparison values and captured failed
rows load directly from customer storage using your Microsoft identity. Your
account needs the corresponding Azure storage permission as well as
General Validation membership.

Continue with [Runs, results, and evidence](/runs-results-and-evidence)
and [When to validate](/when-to-validate) to turn your first check into
a useful control.