DataApps

This page covers on how to manage and use dataapps.

DataApps

DataApps are interactive visualizations built using React, designed to address four main problem types within Rapid Model Recipes: Binary Classification, Regression, Multi-Class Classification, and Binary Experimental.

There are two primary types of DataApps that can be created: Custom DataApps and Import DataApps

Custom DataApps

Custom DataApps come in two variations: Model Independent and Model Dependent (Model DataApp). These DataApps are flexible and can support a variety of data sources, making them versatile for different use cases.

Types of Custom DataApps:

• Project Canvas Datasets: Use datasets available on the project canvas, including user-uploaded datasets. This option also supports interactive data exploration using AskAI.

• Uploaded Datasets: Upload your own datasets and apply AskAI to analyze them, providing an easy way to explore your data without needing a model.

• SQL Sources: Connect to MySQL databases via pre-configured connectors to fetch and analyze data directly from these sources using AskAI.

• Documents and PDFs: Upload documents in formats like PDF, DOC, and DOCX, and use AskAI to query the document contents. This enables quick extraction of insights and analysis of text-based information.

• Prediction Services: Select a pre-configured prediction service linked to your project to query AI models directly via the AskAI interface.

• Scheduler: Choose input datasets, define output datasets, and access reports generated after running jobs. This allows you to run queries on the selected files through AskAI.

• Model: Model DataApps are dependent on a trained model and can only be created if a project includes one. These DataApps focus on visualizing the performance and predictions of the specific model within your project.

Import DataApps

The platform allows you to upload custom DataApps developed with popular frameworks such as ReactJS and Streamlit. After successfully uploading your DataApp, the platform will automatically generate relevant graphs and visualizations based on the integrated data. Import DataApp. To import a DataApp to the platform, see Importing DataApps developed through ReactJS or Streamlit.

Building and Consuming DataApps with Jupyter Notebooks

DataApps can also be built by writing Python code in Jupyter Notebooks, allowing data scientists to create app templates that business users can consume once deployed. Here's how the process works:

• Data Scientist's Role: Data scientists first create an app template in Jupyter Notebook. They then deploy the DataApp by passing a project ID, scenario, artifact, or model.

• Business User's Role: Business users can only view and delete DataApps published to the UI from the Notebook. They cannot create or modify app templates. All app templates created within a tenant are stored in the DataApp module.

Generating Charts:

Users can generate charts by creating custom templates in the Notebook or using existing system templates. Some examples of system templates include:

• Correlation Matrix

• EDA Data Drift

• Pivot Table Viewer

• Visual Analytics

• Pandas Profiler, etc.

Charts can be generated using either a custom or system template, but only the default Streamlit version is supported. In contrast, DataApps support all Streamlit versions.

App Templates: App templates are similar to system templates but are specifically used to generate DataApps (charts).

Dataapps dashboard

Dataapps dashboard has all the dataapps in the form of cards. These dataApps are either created in projects or published from the Notebook. Each card gives various details such as project name, description of the project, recipe used, the person who created the dataapp, last shutdown by, and the date and time at which the dataapp was created. You can also launch the app and relaunch when the app is idle.

Hover-option options on the card

When you hover over a DataApp card, an ellipsis icon appears. Clicking it provides the following options:

• Edit – Modify the DataApp details.

• Delete – Remove the DataApp if it is no longer needed.

• Logs – View the DataApp logs.

• Configs – Monitor memory consumption and CPU usage.

• Consumer Preview – Available only when the DataApp is running, this option lets you preview the consumer interface. Accessible to admins and DataApp power users. You can view this option for all DataApp types excluding Model DataApp and Import DataApp.

• Download Code – Available only for imported external DataApps. Allows you to download the DataApp code to your local system.

• Edit Code -This option is available only for imported ReactJS DataApps. It allows you to edit the underlying ReactJS code to customize the DataApp according to your business requirements. For more information, see Editing the Code of Imported ReactJS DataApp.

Search box

Use the search box to search for Dataapp templates by name.

searchdataapp

List view

The list view provides the Data app details in the table form. You can view the same details that you see in the tile view of Dataapps such as DataApp name, Description, Project, Recipe, Input type, Last Shutdown by, Updated by, Updated on and launch status of the app.

listviewdataapp

Use the table settings icon to rearrange the columns in the order you want and view or hide the columns by selecting and clearing the check boxes next to the columns.

Card view

The card view provides all the data app cards on the dashboard. Click on each card to view the DataApp associated with the project.

Filter dataapps by project

Use the filter option to filer the dataapps by project and view only the dataapps associated with the filtered project on the dataapps dashboard. You cannot view this option in project-level DataApps.

1. Select or clear the projects whose dataapps you want to view or hide.

2. Click Apply.

tablesettings1

Creating a DataApp

Use this procedure to create a DataApp. Depending on your business requirements, you can create different types of custom or model-based DataApps.

• From the Projects Page: DataApps created here are specific to the respective project.

• From the DataApps Page: You can create DataApps for any project within the tenant.

To create a DataApp:

1. Hover over the menu icon and select DataAapps. This shows the DataApps created under this tenant and in different projects.

2. Click the plus button located in the top-right corner of the page, whether you are in the List View or Card View.

createdataappnew

1. Select one of the following options:

• Custom DataApp - Choose this option to create a custom DataApp with your desired input type.

• Import DataApp - Use this option to import a DataApp created in frameworks such as Streamlit or ReactJS.

1. Be it you choose Custom DataApp or Import DataApp, you must select a project in which you want to create the DataApp. This displays the list of projects available within the project.

selectdataapp

1. Click Next to proceed to the Create DataApp page, where you can choose the type of DataApp you want to create. The available types include:

• Project Canvas Datasets. To create a custom DataApp using project canvas datasets as input, see Creating Custom DataApp using project Canvas datasets as input.
• Custom Uploaded Datasets. To create a custom DataApp using custom uploaded datasets as input, see Creating Custom DataApp using Datasets as an input.
• SQL Sources. To create a custom DataApp using SQL source as an input, see Creating Custom DataApp using SQL database as an input.
• Documents and PDFs. To create a custom DataApp using documents and pdfs as an input, see Creating Custom DataApp using Documents and PDFs as an input.
• Prediction Service. To create a custom DataApp using prediction service as an input, see Creating Custom DataApp using Prediction Service as Input Type.
• Scheduler. To create a custom DataApp using scheduler as an input, see Creating Custom DataApp using Scheduler as an input.
• Model DataApp. To create a custom DataApp using model as an input, see Accessing and Creating a Model DataApp at a project level.
• Import DataApp. To import a DataApp to the platform, see Importing DataApps developed through ReactJS or Streamlit.

Editing a DataApp

Use this procedure to delete a DataApp.

To edit a DataApp:

1. Hover over the menu icon and select DataApps. This shows the DataApps created under this tenant and in different projects.

2. Click on the ellipses icon on a DataApp that you want to edit and select the Edit option. This opens the side panel window to make changes to DataApp details.

editdataapp

1. Modify various details of your DataApp, including the name, description, environment settings, models, security configurations, response caching, and model controls. However, please note that the input type chosen during the creation of the DataApp cannot be edited.

2. Click Save to update the changes.

editdataapp_new

Deleting a DataApp

Use this procedure to delete a DataApp.

To delete a DataApp:

1. From the project left navigation menu, select DataApps. The DataApps dashboard is displayed.

2. Click the ellipses icon on the DataApps dashboard.

deletedataapps

1. Click Delete. The dialog box appears prompting you to delete or discard

2. Click Yes, Delete to delete the DataApp permanently.

Viewing DataApp logs

Use the history of DataApp logs to debug the issues in DataApp.

To view DataApp logs:

1. From the left navigation menu, select DataApps. The DataApps dashboard is displayed.

2. Click the ellipses icon on the DataApps dashboard.

3. Click Logs. The logs side panel appears. You can search for the log data you want in the search box.

viewlogs_dataapps

You can also click on the kebab menu to view two options:

• Select Export to export the logs to the text file.

• Select Open in New Tab to open the logs in a new tab.

Configuring DataApp Shutdown Time

Use this procedure to configure the shutdown time for DataApp. You can also check resource consumption while DataApp is running.

To view DataApp logs:

1. From the left navigation menu, select DataApps. The DataApps dashboard is displayed.

2. Click the ellipses icon on the DataApps dashboard.

3. Click Configs.

configdataapps

The Configuration & Consumption side-panel appears.

1. Select the time period (in hours) after which the DataApp should automatically shut down if it remains inactive.

2. Select Evergreen check box to keep the DataApp Running always.

3. Clear this check box to specify the time after which the DataApp must shut down if there is no activity. You can set the time in hours.

4. Click Save.

configurationfordataapp

Editing the Chart Output in DataApps

After generating the chart, you can use the edit option to customize it. This allows you to modify elements such as the chart's colors, type, and title. Follow the steps below to edit your chart:

1. Enter a prompt to generate the chart in the AskAI tab of DataApps. You can use the slash option to select the output type, then type your query.

2. Click the Edit option on the chart to open the Chart Edit window.

3. Enter the prompt on how you want the chart to be modified. Here, we are entering the query to make the chart colorful and change its title to "Number of passengers by Survival status."

   You can now see the chart color and title being updated in the screenshot below:

4. Click Save to save the changes to the chart.