--- source: https://qlik.dev/embed/qlik-embed/quickstart/qlik-embed-impersonation-tutorial/ last_updated: 2026-03-25T16:41:23+01:00 --- # Embed Qlik analytics and Qlik Answers using qlik-embed and OAuth impersonation ## Overview This tutorial shows how to deploy analytics and AI into your solution with a seamless login experience for your users, even when your web app or portal does not have a backend identity provider for user authentication. > **Notes:** > > - This tutorial is based on version [v3.1.0](https://github.com/qlik-oss/qlik-cloud-embed-oauth-impersonation/tree/v3.1.0) > of the project repository. > - **This project is not production-ready**. It is structured for learning and evaluating qlik-embed with a simple > OAuth impersonation configuration. > - For a production app: > > - Review the [guiding principles for OAuth impersonation](https://qlik.dev/authenticate/oauth/guiding-principles-oauth-impersonation/) > as well as the documentation for [qlik-embed](https://qlik.dev/embed/qlik-embed/) and [qlik/api](https://qlik.dev/toolkits/qlik-api/). > - Use HTTPS rather than HTTP. This project leverages qlik-embed, qlik/api, and OAuth machine-to-machine impersonation capabilities. It showcases several embedding techniques, such as: - qlik-embed `classic/app`: full sheet embed supporting the native experience. - qlik-embed `analytics/sheet`: lightweight full sheet embed. - qlik-embed `classic/chart`: load legacy charts in a similar manner to `classic/app`. - qlik-embed `analytics/chart`: lightweight charts in a similar manner to `analytics/sheet`. - qlik-embed `analytics/chart` on-the-fly: lightweight charts generated on-the-fly (the chart doesn't need to be in the Qlik Sense app, it is defined in the web app instead). - qlik-embed `ai/assistant`: provides access to AI assistants in Qlik Answers. - qlik-embed `ai/agentic-assistant`: provides access to agentic assistants in Qlik Answers. - qlik-embed `analytics/field`: lightweight way to render a list box containing dimension values. - qlik-embed `analytics/selections`: lightweight way to render a full Qlik Sense selections bar. - qlik-embed retrieval of hypercube data from an existing object. - qlik/api retrieval of hypercube data without an existing qlik-embed object. ## What you'll learn By the end of this step-by-step tutorial, you'll have: - Embedded Qlik Sense analytics into your solution using various qlik-embed techniques. - Configured OAuth impersonation for a seamless user login experience. - Deployed a working example of an embedded Qlik Sense app. ## Prerequisites - [Node.js](https://nodejs.org) version 20 or higher. - A backend [OAuth M2M client](https://qlik.dev/authenticate/oauth/create/create-oauth-client/) with scopes `user_default` and `admin_classic`, and allowed origins set to `http://localhost:3000`. - A frontend [OAuth M2M impersonation client](https://qlik.dev/authenticate/oauth/create/create-oauth-client-m2m-impersonation/) with scope `user_default`, and allowed origins set to `http://localhost:3000`. ## Step 1: Set up your local project In this step, you'll set up a local development environment by cloning the GitHub repository or downloading the project files. ### Method 1: Clone the GitHub repository Clone the GitHub repository using the `git clone` command. ```shell git clone https://github.com/qlik-oss/qlik-cloud-embed-oauth-impersonation.git ``` ### Method 2: Download and extract the project files Alternatively, you can download and extract the project files. 1. On the project's [GitHub page](https://github.com/qlik-oss/qlik-cloud-embed-oauth-impersonation), click **Code**. 2. Select **Download ZIP**. 3. Extract the content of the ZIP file in the folder of your choice. ## Step 2: Upload the demo Qlik Sense app In this step, you'll upload a demo Qlik Sense app that serves as the data source for the embedded analytics examples. 1. Upload the [demo Qlik Sense app](https://github.com/qlik-oss/qlik-cloud-embed-oauth-impersonation/blob/main/qlik_app/Consumer%20Sales.qvf) to your tenant. 2. Open the app and copy the ID (it will be a GUID similar to `946d5af4-e089-42d3-9ba7-1d21adb68472`). > **Note:** The project files contain some hard-coded values for this demo Qlik Sense app. 3. Move the app to a new `shared` space. 4. Edit the space configuration to provide `Can view` access to anyone in the tenant. > **Note:** In a production deployment, ensure the logged-in user has access to the app. ## Step 3 (optional): Create a Qlik Answers assistant In this optional step, you'll create a Qlik Answers assistant that allows users to interact with indexed knowledgebase content using natural language questions. > **Cross-region inference required:** To use the agentic Qlik Answers experience, you must opt in to cross-region inference. > This allows Qlik Cloud to temporarily process data outside your tenant region. > For more information, see the [Qlik Answers documentation](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/QlikAnswers/Qlik-Answers.htm) on Qlik Help. 1. Follow the [Qlik Answers documentation](https://help.qlik.com/en-US/cloud-services/Subsystems/Hub/Content/Sense_Hub/QlikAnswers/Qlik-Answers.htm) on Qlik Help to set up a new knowledgebase and assistant, and index the knowledgebase data ready for users to ask questions. 2. Provide `View` and `Can consume data` roles to all users in the tenant for the spaces containing the knowledgebase, assistant, and any data connections used by the knowledgebase. ## Step 4: Set up environment variables In this step, you'll configure environment variables to securely store sensitive information and connect to required resources. 1. Rename the `template.env` file to `.env`. 2. Edit the `.env` file with values that match your Qlik Cloud deployment. - `OAUTH_BACKEND_CLIENT_ID` and `OAUTH_BACKEND_CLIENT_SECRET`: credentials for the backend OAuth M2M client. - `OAUTH_FRONTEND_CLIENT_ID` and `OAUTH_FRONTEND_CLIENT_SECRET`: credentials for the frontend OAuth M2M impersonation client. > **Note:** Keep these secrets safe as they provide wide access to your tenant. - `TENANT_URI`: the hostname of your Qlik Cloud tenant, for example `z29kgagw312sl0g.eu.qlikcloud.com` (required). - `APP_ID`: the GUID for the Qlik Sense app you uploaded to your tenant. - `ASSISTANT_ID`: the GUID of the Qlik Answers assistant you wish to embed. Leave blank to omit this UI. - `AGENTIC_ASSISTANT_ID`: the GUID of the Qlik Answers agentic assistant you wish to embed. Leave blank to omit this UI. 3. (Optional) If you are using an app other than the provided demo Qlik Sense application, add the following optional variables to `.env` to configure embedded examples: - `SHEET_ID`: a sheet ID from your app (analytics/sheet and classic/app examples). - `OBJECT_ID`: a chart/object ID from your app (analytics/chart and classic/chart examples). - `FIELD_ID`: a field name from your app (filter pane example). - `HYPERCUBE_DIMENSION`: field to use as the hypercube dimension (data example). - `HYPERCUBE_MEASURE`: measure expression to use for the hypercube (data example). - `MASTER_DIMENSION` and `MASTER_MEASURE`: master items used by the on-the-fly chart example. 4. (Optional) If you wish to further configure your web app and integration, update these values in `.env`. - `SESSION_SECRET`: specify a random long string that will be used to sign the session. - `PORT`: port the web app listens on (defaults to `3000`). - `USER_PREFIX`: prefix used when the app creates demo users. ## Step 5: Install the dependencies and run the app Now that the project is configured, you can install the required dependencies and run the app locally to view the embedded analytics. 1. Open a terminal window and navigate to the folder containing the project files you extracted or cloned. ```shell cd ``` 2. Install dependencies. ```shell npm install ``` 3. Start the server: ```shell npm start ``` 4. Open `http://localhost:3000` in your browser. You should see your web app running locally with embedded Qlik Sense analytics rendered using various qlik-embed techniques. [image: Screenshot of a web app displaying embedded Qlik Sense analytics] ## Troubleshooting - If the app does not load, verify the environment variable values configured in [step 4](#step-4-set-up-environment-variables) and review any error messages in the terminal. - If you get authorization errors, verify the scopes configured for your OAuth M2M clients. ## Next steps Now that you have a working example, you can experiment with other [qlik-embed parameters](https://qlik.dev/embed/qlik-embed/parameters/).