Scheduler

Creating Custom DataApp using Scheduler as an input

Use this procedure to create a custom DataApp using job an an input. Note that these DataApps are model-independent, so no project model is required to create this type of custom DataApp.

Note: Ensure that at least one job has been created and run successfully, with datasets in a built state. Without a successful job run, the datasets will not be available for selection or for executing prompts.

1. Hover over the menu icon and select Projects

2. Select the project for which you want to create DataApps and click the DataApps icon from the project level navigation.

3. Click the plus icon and select Custom DataApp. This opens the Create DataApp page.

Details Tab

1. Specify this information on the Details tab.

2. Select the input type as Scheduler.

3. Add the description of the DataApp that explains about it.

4. By default, the environment selected during project creation is applied. However, you have the flexibility to choose a different environment for running your DataApps.

5. Provide the name of the DataApp on the breadcrumb.

6. Click to upload an image to display on the DataApp card that you see on the DataApps page.

Settings Tab

1. Click the Settings tab and specify this information.

2. Select a model that you want to use in the Custom DataApp. Possible values:

   • OpenAI GPT-4o (by default this is selected)

   • OpenAI GPT-4 Turbo

   • Azure OpenAI GPT-4o

   • Anthropic Claude 3.5 Sonnet (beta)

3. Select the job on which you want to create the DataApp from the list of jobs created in the project.

4. Toggle ON the Enable Response Caching option to return the same response for the identical queries despite asking multiple times.

5. Toggle ON the Show Model Response Code option to view the code generated by the model in response to the queries.

6. Enable Allow Column Hyperlinks to create hyperlinks between columns in related tables.

7. Select Access Control to manage access to chats and charts generated within the DataApp. The available options are:

   • Team Access: Allows all users within the tenant to view chats and charts in the DataApp.

   • Individual Access: Restricts visibility of chats and charts to users who created them. For example, if User A creates Chat A and Chart C, only User A can view these.

8. Select the Security options. Possible values:

   • Sample Data : The sample of 5 rows of data is shared with the LLM for context.

   • Only Metadata: Only the column names in the dataset are shared with the LLM for context.

9. Enter Model controls in the text box to provide specific context to the AI guide. This helps in aligning the AI-generated responses more closely with the user’s particular use case.

10. Toggle ON the Enable Insights Model to activate reasoning support for dataset and chart outputs in response to user queries on the AskAI tab. For more information, refer Enabling the Insights Model to View Contextual Insights in AskAI section.
11. When the Enable Insights Model toggle is turned on, two additional configuration options appear:

    • Insights Model: Select the model that will interpret and generate insights from the dataset or chart outputs.

    • System Message: Optionally provide contextual guidance to the model, helping it tailor responses based on your specific use case or analytical objectives.

12. Turn ON or OFF the following toggles in the Consumer Permissions section to control what actions users with the DataApp Consumer role can perform:

    • Allow New Chat Creation: Turn ON to allow consumers to create new chats in the AskAI tab.

    • Allow Chat Deletion: Turn ON to enable consumers to delete chat threads.

    • Allow Input Selection: Turn ON to allow consumers to select input datasets or reports for chats in AskAI.

    • Show Input Name & Details: This option is disabled by default and is automatically enabled when Allow Input Selection is turned OFF. When enabled, consumers can view input data and its details. Ensure at least one input is selected in the chat for consumers to ask prompts related to the selected input. If a consumer deletes a chat, the same input will automatically be transferred to the new chat, ensuring continuity and ease of use.

    • Allow Slash Options: Turn ON to enable consumers use slash commands in the AskAI query box to specify the desired output type—datasets, text, charts, or prompt suggestions—allowing for more precise queries and seamless interaction with data.

    • Show Scheduler Charts Tab: Turn ON to allow consumers to view the Scheduler Charts tab.

    • Show Model Response Code: Turn ON to allow consumers to view the model-generated code for their queries.

    • Hide Side Panel: If toggles such as Allow New Chat Creation, Show User Charts Tab, Allow Input Selection, and Allow Chat Deletion are turned OFF, the side panel will no longer be visible.

If you want to preview how the DataApp's consumer interface appears after adjusting these toggles, use the Consumer Preview option. You can find this option under the Actions drop-down on the DataApps page. This allows you to see the interface from a consumer’s perspective and ensure that the changes reflect as expected. See Previewing the Consumer Interface.

Starter Prompts

Adding Starter Prompts in DataApps

Starter prompts help new DataApp users get started by providing predefined queries on the AskAI page. Users can add up to 10 prompts to guide interactions with AI-powered DataApps, making it easier for business users to formulate relevant queries.

Steps to Add Starter Prompts

1. Click the Starter Prompts tab.

2. In the Create New Prompt section, enter the prompt you want to display on the AskAI page.

3. Click +Add Prompt after each entry. You can add up to 10 prompts per DataApp.

Once added, these prompts will appear in the AskAI window, providing users with helpful starting points for their queries.

Note: Starter prompts can be added for all types of custom DataApps, except for model DataApps and imported DataApps.

1. Click Create. The DataApp card is created.

datasetinputjob

1. Click on the DataApp card to launch the AskAI DataApp. The AskAI chat window appears.

2. Click Select Dataset to Start in the prompt box drop-down and select the dataset you want. All the datasets you are viewing in the drop-down are the input and output datasets generated after the latest job run.

datasetinputjob1

Once you select the dataset, this loads the data onto the chat window. Use the Schema option to view the data type of each column.

1. Enter your query in the query box and use a slash (/) to select the type of output you want the AI to generate, such as text, dataset, or chart.

Once the output is generated, you can:

• Copy the answer using the Copy Answer option.

• View the generated code by selecting the View Code option.

• Get an explanation for each line of code by using the Explain option, which becomes visible only after clicking View Code.

You can also choose from prompt suggestions tailored to the selected dataset.

Note:

• If you select prompt suggestions, AskAI will provide five relevant prompts. You can either copy a suggestion into the query box or run it directly using the Run button.

• If you have an existing AskAI chat created to query input and output datasets or other job-generated outputs, the chat will continue to reference datasets from the previous job run. To query the latest scheduler inputs and outputs, you will need to create a new chat each time.

• Alternatively, within a Scheduler DataApp, you can use the Click here option (next to the output selector) when a new output is generated while a previous chat is still open. Clicking it reloads the latest data and re-triggers all LLM queries to reflect updated inputs. Note that results may vary or temporarily fail due to data changes.

1. Click the Scheduler Charts tab to add charts generated after the schedule run in this tab.

2. Click Add Charts from Scheduler to add charts. You can choose the charts you want to add to the DataApp if there are multiple charts generated.

jobscharts

1. Click Add Chart To DataApp next to the chart you want to add. However, if you no longer want this chart in the Job Charts tab, you can use Remove From DataApp to remove it.

Note: Charts are displayed only if the data pipeline generates chart outputs. Furthermore, once a chart output is created after running a query, it cannot be edited like other DataApp input types—for example, modifying the title or changing colors.

Perform the following actions clicking the Actions drop-down:

• Modify the DataApp details, using the Edit option. For more details, see Editing a DataApp section.
• Copy the dataapps URL to share with the other business users, using the Copy option.

• Open the dataapps on a new tab, using the Open in New Tab option.

• Configure the shutdown time of the DataApp, using the Config option. See configuring shutdown time of the DataApp section for more details.
• View logs of DataApps to debug issues, using the Logs option.

• Delete the DataApp that is no longer required, using the Delete option.

• Customize the branding appearance of your DataApp, using the Branding option. This opens the Branding modal. Enter your desired title in the DataApp Title field, then use the Upload from Computer option to upload your logo. Once you have added the title and logo, click Save to apply the changes. The customized title and logo will now appear on the AskAI page and will also be visible when the DataApp is opened in a new tab.

• As a DataApp power user or admin, you can preview the consumer interface using the Consumer Preview option. This option is available only when the DataApp is running.