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With the new inclusion of the Get Chart Image block in the Qlik Reporting connector in Qlik Application Automation, you now have more options to notify a group of users with more in-depth data and charts using Slack, Microsoft Teams, and email.
This article will guide you in sending your first chart image to Slack with Qlik Application Automation.
It explains a basic example of a template configured in Qlik Application Automation for this scenario.
You can make use of the template which is available in the template picker. You can find it by navigating to Add new -> New automation -> Search templates and searching for 'Send a Chart Image to Slack' in the search bar, and clicking the Use template option.
For guidance on sending charts via Microsoft Teams and mail, go to the "Next Steps" section at the end of this article.
You can download examples of the automations from this article: Send-chart-image-to-slack.json, Send-chart-image-to-outlook.json, Send-chart-image-to-mail.json, Send-chart-image-to-microsoft-teams.json
Warning: Whenever the “Get Chart Image” block is to be used, we advise you to only use it with temporary bookmarks or pre-existing persistent bookmarks.
If the condition block outcome evaluates to false:
The information in this article is provided as-is and will be used at your discretion. Depending on the tool(s) used, customization(s), and/or other factors, ongoing support on the solution below may not be provided by Qlik Support.
This article gives an overview of the available blocks in the Jira connector in Qlik Application Automation. It will also go over some basic examples of retrieving issues by a specified project and creating an issue within a Jira account.
This connector supports CRUD operations(read, create, update, delete) for the following modules in Jira:
There are also a few generic blocks that could help to cover the other modules :
Authentication for this connector is based on the oAuth2 Protocol.
Let's now go over a few basic examples of how to use the Jira connector:
1. How to list issues from a specific project from a Jira account
2. To create a new issue:
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
This article explains how the Reporting connector in Qlik Application Automation can be used to generate multi-app reports. It also explains how the generated report can be stored on a cloud storage tool, like Microsoft SharePoint.
Multi-app reports
A multi-app report is a report that contains sheets from multiple apps. This type of report can be created in Qlik Application Automation with the Create Multi App Report and the Add Sheet to Multi App Report blocks.
To add selections to these sheets, you can still use the Add Selection To Sheet block. To add selections to the report, you can use the Add Selection To Report block.
Example
In this example, we'll create an automation that generates a report containing two sheets from two different apps, with selections applied to the second sheet.
Before you continue, please create a new automation and search for the reporting connector in the Block Library:
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
Installing, upgrading, and managing the Qlik Cloud Monitoring Apps has just gotten a whole lot easier! With two new Qlik Application Automation templates coupled with Qlik Data Alerts, you can now:
The above allows you to deploy the monitoring apps to your tenant with a hands-off approach. Dive into the individual components below.
Some monitoring apps are designed for specific Qlik Cloud subscription types. Refer to the compatibility matrix within the Qlik Cloud Monitoring Apps repository.
Content:
This automation template is a fully guided installer/updater for the Qlik Cloud Monitoring Applications, including but not limited to the App Analyzer, Entitlement Analyzer, Reload Analyzer, and Access Evaluator applications. Leverage this automation template to quickly and easily install and update these or a subset of these applications with all their dependencies. The applications themselves are community-supported; and, they are provided through Qlik's Open-Source Software GitHub and thus are subject to Qlik's open-source guidelines and policies.
For more information, refer to the GitHub repository.
Note that if the monitoring applications have been installed manually (i.e., not through this automation) then they will not be detected as existing. The automation will install new copies side-by-side. Any subsequent executions of the automation will detect the newly installed monitoring applications and check their versions, etc. This is due to the fact that the applications are tagged with "QCMA - {appName}" and "QCMA - {version}" during the installation process through the automation. Manually installed applications will not have these tags and therefore will not be detected.
This template is intended to be used alongside the Qlik Cloud Monitoring Apps for user-based subscriptions template. This automation provides the ability to keep the API key and associated data connection used for the Qlik Cloud Monitoring Apps up to date on a scheduled basis. Simply input the space Id where the monitoring_apps_REST data connection should reside, and the automation will recreate both the API key and data connection regularly. Ensure that the cadence of the automation’s schedule is less than the expiry of the API key.
Enter in the Id of the space where the monitoring_apps_REST data connection should reside.
Ensure that this automation is run off-hours from your scheduled monitoring application reloads so it does not disrupt the reload process.
Each Qlik Cloud Monitoring App has the following two variables:
With these variables, we can create a new Qlik Data Alert on a per-app basis. For each monitoring app that you want to be notified on if it falls out of date:
Here is an example of an alert received for the App Analyzer, showing that at this point in time, the latest version of the application is 5.1.3 and that the app is out of date:
Q: Can I re-run the installer to check if any of the monitoring applications are able to be upgraded to a later version?
A: Yes. Run the installer, select which applications should be checked and select the space that they reside in. If any of the selected applications are not installed or are upgradeable, a prompt will appear to continue to install/upgrade for the relevant applications.
Q: What if multiple people install monitoring applications in different spaces?
A: The template scopes the applications install process to a “target” space, i.e., a shared space (if not published) or a managed space. It will scope the API key name to `QCMA – {spaceId}` of that target space. This allows the template to install/update the monitoring applications across spaces and across users. If one user installs an application to “Space A” and then another user installs a different monitoring application to “Space A”, the template will see that a data connection and associated API key (in this case from another user) exists for that space already and it will install the application leveraging those pre-existing assets.
Q: What if a new monitoring application is released? Will the template provide the ability to install that application as well?
A: Yes. The template receives the list of applications dynamically from GitHub. If a new monitoring application is released, it will become available immediately through the template.
Q: I would like to be notified whenever a new version of a monitoring applications is released. Can this template do that?
A: As per the article above, the automation templates are not responsible for notifications of whether the applications are out of date. This is achieved using Qlik Alerting on a per-application basis as described in Part 3.
Q:I have updated my application, but I noticed that it did not preserve the history. Why is that?
A: The history is preserved in the prior versions of the application’s QVDs so the data is never deleted and can be loaded into the older version. Each upgrade will generate a new set of QVDs as the data models for the applications sometimes change due to bug fixes, updates, new features, etc. If you want to preserve the history when updating, the application can be upgraded with the “Publish side-by-side” method so that the older version of the application will remain as an archival application. However note that the Qlik Alert (from Part 3) will need to be recreated and any community content that was created on the older application will not be transferred to the new application.
With Qlik Application Automation, you can get data out of Qlik Cloud and distributing it to different users in formatted Excel. The workflow can be automated by leveraging the connectors for Office 365, specifically Microsoft SharePoint and Microsoft Excel.
Here I share two example Qlik Application Automation workspaces that you can use and modify to suit your requirements.
Content:
Video:
Note - These instructions assume you have already created connections as required in Example 1.
This On-Demand Report Automation can be used across multiple apps and tables. Simply copy the extension object between apps & sheets, and update the Object ID (Measure 3) for each instance.
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
This article provides an overview of how to manage users using Qlik Application Automation. This approach can be useful when migrating from QlikView, or Qlik Sense Client Managed, to Qlik Sense Cloud when security concerns prevent the usage of Qlik-CLI and PowerShell scripting.
You will find an automation attached to this article that works with the Microsoft Excel connector. More information on importing automation can be found here.
Content
In this example, we use a Microsoft Excel file as a source file to manage users. A sheet name, for example, Users, must be added and this must also be provided as input when running the automation. The sheet must also contain these headers: userId, Name, Subject, Email, Roles, Licence, and Flag.
Example of sheet configuration:
If users are to be created the Flag column must be set to create. If users are to be deleted, there's no need to include roles, but Flag must be set to delete.
Add the List Rows With Headers block from the Microsoft Excel connector to read the values that have been configured in the Excel sheet.
When running the automation you must provide input to the automation, this includes the name of the worksheet to read data from. You also need to specify the first and last cell to read data from, as well as if users are to be created or deleted. Example :
Input | Value |
Worksheet Name | Users |
Excel Start Cell | A1 |
Excel End Cell | G5 |
Mode | Create |
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
How to manage space membership (users)
This article provides a step-by-step guide on building a write back solution with only native Qlik components and automations.
Content:
Disclaimer for reporting use cases: this solution could produce inconsistent results in reports produced with automations; when using the button to pass through selections, the intended report composition and associated data reduction for the report may not be achieved. This is due to the fact that the session state of Qlik Application Automation cannot be transferred to the report composition definition that is passed to the Qlik Reporting Service.
When analyzing results in a Qlik Sense app, it could happen you spot a mistake in your data or something that seems odd. To address this, you may want someone from your team to investigate this or you may want to update data in your source systems directly without leaving Qlik. Or maybe your data is just fine but you want to add a new record from within Qlik without having to open your business application. These scenarios fit in the following use cases:
This is the least intrusive form of writing back that delegates the change to someone in your data team. The idea is that you create a ticket in a task management system like Jira or ServiceNow. Someone from your team will then pick up the ticket, investigate your comment, and review the data. The difference with sending an alert or email is that the ticketing system guarantees that the request is tracked.
Another option to communicate changes is to write a comment or a tag for one or more records directly to the source system. This could be a comment on a deal record in your CRM or it could be stored in a separate database table if you're loading data from a database.
The final use case allows for updating records directly from within the sheet. Make sure you know who has access to the button before setting this up since this will allow users to change records directly.
All the above use cases can be realized in the same way: by configuring a native Qlik Sense button in your sheet to run an automation. Before you start this tutorial, make sure you already have an app and a new, empty automation. The tutorial has 2 parts:
To configure the app, we'll use the following native Qlik Sense components:
Steps:
Enable the "Show notifications" toggle, this will send a toast notification back to the user in the sheet after the automation completes. Feel free to increase the duration.
Tip: using a Container component will allow your variable inputs & button to scale better for smaller screens.
Upon automation run, this will resolve to the first text value selected for the field hs_object_id (which corresponds to the deal ID from HubSpot). To update this to a comma-separated list of IDs, the mapping must first be changed to output a list of all values for hs_object_id. To do this, toggle the formula parsing:
Bonus: add a link to the toast notification
Instead of showing a plain message in the toast notification, it's also possible to include a link to point the user to a certain resource. This can be done by configuring the Update Run Title block with the following snippet:
{"message":"Ticket created", "url": "https://<link to jira ticket>"}
Depending on the button's configuration and the automation run mode, use either the Update Run Title block or the Output block to show the toast notification.
See the below table for each option:
Run mode configuration in the automation | Run mode in the button | Block for toast notification | Who can see the notification |
Triggered async | Triggered | Update Run Title | Automation owner only |
Triggered sync | Triggered | Output | Everyone |
Triggered sync | Not triggered | Update Run Title | Automation owner only |
The run mode in the button can be configured by toggling the 'Run mode: triggered' option in the button's settings:
The run mode in the automation can be configured here in the Start block:
After writing back to your source systems, you'll want to do a reload to see your changes reflected in the app. Be mindful of the impact of doing these reloads. If multiple people are using this button at the same time, you don't want to do a reload for each update.
Problems:
Improvements:
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
This article gives an overview of the available blocks in the Monday.com connector in Qlik Application Automation, as well as expand on basic example use-cases.
Monday.com is a powerful project management system — a complete Work OS designed to help your team complete projects efficiently, collaborate effectively, and grow online. And Qlik Application Automation supports implementations involving Monday.com.
Content:
Assets
Boards
Column
Folders
Groups
Items
Notifications
Raw API
Tags
Teams
Updates
Users
Workspaces
Similar use-cases can be implemented with other ITSM tools like Service-Now etc.
This article explains how the Qlik Reporting connector in Qlik Application Automation can be used to generate a bursted report that delivers recipient-specific data.
For more information on the Qlik Reporting connector, see this Reporting tutorial.
This article offers two examples where the recipient list and field for reduction are captured in an XLS file or a straight table in an app. Qlik Application Automation allows you to connect to a variety of data sources, including databases, cloud storage locations, and more. This allows you to store your recipient lists in the appropriate location and apply the concepts found in the examples below to create your reporting automation. By configuring the Start block's run mode, the reporting automations can be scheduled or driven from other business processes.
In this example, the email addresses of the recipients are stored in a straight table. Add a private sheet to your app and add a straight table to it. This table should contain the recipients' email address, name, and a value to reduce the app on. We won't go over the step-by-step creation of this automation since it's available as a template in the template picker under the name "Send a burst report to email recipients from a straight table".
Instead, a few key blocks of this template are discussed below.
In this example, the email addresses of the recipients are stored in an Excel file. This can be a simple file that contains one worksheet with headers on the first row (name, email & a value for reduction) and one record on each subsequent row.
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
To help Qlik customers manage costs more effectively, Qlik has developed the Qlik Snowflake Monitoring application, designed to provide invaluable insights about your Snowflake costs, usage, inventory, security, performance and contract utilization. This app utilizes Qlik's Associative Engine to connect directly to your Snowflake instance and reveal insights from Snowflake's detailed metadata, offering valuable information that traditional query-based tools and Snowflake's own reports are unable to provide.
Leveraging Qlik Application Automation, and Data Alerts, you can:
*Minor configuration is required on first run to create the required data connections.
Content:
This automation template is a fully guided installer/updater for the Qlik Snowflake Monitor. Leverage this automation template to easily install and update this application. The application itself is community-supported; and it is provided through Qlik’s Open-Source Software GitHub and thus is subject to Qlik’s open-source guidelines & policies.
For more information, refer to the GitHub Repository.
If the monitoring app was installed manually (i.e. not through the application automation installer), then the app will not be detected as existing. The automation will install new copies side-by-side. Any subsequent executions of the automation will detect the newly installed monitoring application and check their versions. This is because the application is tagged with ‘QCS - QSM - {App Name}’ and ‘QCS – QSM - {Version}’ during the installation process through the automation. Manually installed applications will not have these tags and therefore will not be detected.
The Qlik Snowflake Monitor requires two connections, one to your Snowflake instance to feed the data for your analytics, and one REST connection to the qlik-oss repository to run a version check on the monitor.
You will need to create a custom User, Role and Warehouse on your snowflake tenant. This is to ensure this user and role can see the monitoring details and can be monitored.
For Authentication, this setup is defaulted to username & password.
Finally, you need to name the connection as follows:
If you wish to use an alternative authentication method, please follow the documentation accordingly on both Snowflake & Qlik.
The REST connection is used to fetch version details from the GitHub repository. On reload it will look for the the latest released version in github and check this against the version you have installed. You can later use this in ‘Part Three’ to create an alert when updates to the application are available. To create a REST connection the following information is required:
Once these two connections have been set up, you can reload the application. The application has been created to accommodate Snowflake tenants of all sizes. If you have a small tenant, you will find the initial run of the load script can take around 30 minutes, and for larger tenants this can be over an hour or two. Subsequent runs will utilize cached QVDs that update daily to reduce reload times each subsequent day.
If a new release of the application is made, occasionally a full reload of data is required, but generally, if the data schema is unchanged the existing QVDs will be maintained. This is through the use of versions in the names of the QVDs used to store the data.
The application has the following two variables:
To create a new Data Alert for updates to the monitoring app, follow these steps:
The Qlik Snowflake Monitor can be easily installed by following these steps above. If you wish to find out more, check out this Ometis blog post and this Ometis Webinar to get a run through of the analytics this application can offer.
If you face any issues, please use the GitHub and raise an issue through the repository.
This article gives an overview of the available blocks in the Github connector in Qlik Application Automation. It will also go over some basic examples of retrieving file/blob contents from your repos as well as other functionalities within a GitHub account.
As with most connectors provided for automations the authentication for this connector is based on the oAuth2 Protocol, so when connecting to it you provide the user name and password of the account directly to the Github platform to request access so it is done in the most secure manner there is.
Let's now go over a few basic examples of how to use the Github connector:
How to list owned repositories and check their contents from your Github account:
Now the "list my repositories" block offers a couple of filtering options depending what result you want (all repos or just the private or public ones and if you want the result to come in sorted by some rule) but they are mostly optional. Not filling them in will return by default all repositories.
As for the "List repository contents" block you will need to fill in the username you use for your github account as well as the repository name which can be filled in with the results gotten from the first block. You can leave the path parameter empty to get the contents from the root folder or you can specify a path and the contents of that path will be returned.
As stated, if you expect to retrieve only one record, the use of "get repository content" block is more better suited. Also, you might want to switch this "List repository contents" block On Error status to either warning or ignore since Github API platform returns a 404 error if one of the queried repositories is empty.
Now if you are planning to use the "Get repository content" block another warning should be mentioned and that this block only works for files or blobs up to a maximum of 1 MB in size, as per Githubs platform limitations. The response of this block should look like:
As you can see we have a couple of information stubs of that file, but most importantly from here is the SHA property, which is needed if you are planning to later on use the "Create or update file contents" block, required input parameter for the update of a file/blob.
Now if you're planning on updating files that are bigger than 1MB and you require the SHA of that file, we suggest using the list repository contents block and search for the required file and SHA in that result.
As for other functionalities of the Github connector we support also getting and listing commits or issues present in a repository, listing of users and many other requests but, if you are in need of a request that isn't present, we also offer the functionality to create your own requests to the Github API by making use of the RAW API blocks. These API blocks and their uses are explained in a separate article.
You can find attached to this article a simple JSON example which you can upload to your workspace, if you want to see a quick example of how to use version control to back up your QCS apps I suggest visiting the related article.
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
How to: Qlik Application Automation for backing up and versioning Qlik Cloud apps on Github
This article covers the usage of the Qlik Application Automation cloud storage blocks and gives design flow examples which apply them. You can also download an example JSON using Google Cloud Storage, and we have compiled a list of links for more in-depth platform connections and atypical usages.
Content
Selecting Cloud storage when creating your automation will present you with the following list:
Here is an example of how to verify if a file exists prior to creating a new one. This is specifically important when you set up an automation meant to save your result in a target file that might or might not be at the location suggested. Since you cannot create a new file if a previous one exists, you will need to apply the following to your automation:
You can verify if the file exists initially, and, based on the response from that block, either simply create a new file or delete the old file and create a new one to write data to.
And last but not least, this is a list of supported platforms for the native blocks as well as links to how to connect to them as well as more quirky details they have.
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
Inside Qlik Application Automation, the Amazon S3 functionality is split into two connectors: the native Cloud Storage connector and the specific Amazon S3 connector. To create, update, and delete files, it’s highly recommended to use the native Cloud Storage connector. To get the information and metadata of regions & buckets, use the Amazon S3 connector.
The following is an example of automation using the Amazon S3 connector to output a paginated list of regions and buckets in each region (not covered in this article).
This article focuses on the available blocks in the native Cloud Storage connector in Qlik Application Automation to work with files stored in S3 buckets. It will provide some examples of basic operations such as listing files in a bucket, opening a file, reading from an existing file, creating a new file in a bucket, and writing lines to an existing file.
The Cloud Storage connector supports additional building blocks to copy files, move files, and check if a file already exists in a bucket, which can help with additional use cases. The Amazon S3 connection also supports advanced use cases such as generating a URL that grants temporary access to an S3 object, or downloading a file from a public URL and uploading this to Amazon S3.
Let’s get started.
Authentication for this connector is based on tokens or keys.
Log in to the AWS console with an IAM user to generate the access key ID and secret access key required to authenticate.
Now let's go over the basic use cases and the supporting building blocks in the Cloud Storage connector to work with Amazon S3:
The Amazon S3 connector in Qlik Application Automation now supports adding the SSE header value for creating new files. This header is available on the Create File and Copy File blocks. It's possible to choose the default behavior which is AES256 encryption. As an alternative, it's possible to choose aws:kms encryption and provide a valid KMS Key ID.
Attached example file: create_and_write_files_amazon_s3.json
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
It is possible to export the list of tenatnt users to a .json file using the "user ls" command from the Qlik Command Line Interface (qlik-cli).
The scripts provided in this article are provided as they are and they are for guidance only.
As a tenant admin, download and configure the Qlik-cli
qlik user ls --limit 1000 > tenantusers.json
[
{
"assignedGroups": [],
"assignedRoles": [
{
"id": "608050f7634644db3678b1a2",
"level": "user",
"name": "Developer",
"type": "default"
},
{
"id": "608050f7634644db3678b17f",
"level": "admin",
"name": "TenantAdmin",
"type": "default"
},
{
"id": "605a1c2151382ffc836af862",
"level": "user",
"name": "SharedSpaceCreator",
"type": "default"
},
{
"id": "605a1c2151382ffc836af866",
"level": "user",
"name": "ManagedSpaceCreator",
"type": "default"
},
{
"id": "605a1c2151382ffc836af86b",
"level": "user",
"name": "DataSpaceCreator",
"type": "default"
},
{
"id": "605a1c2151382ffc836af85d",
"level": "admin",
"name": "AnalyticsAdmin",
"type": "default"
},
{
"id": "605a1c2151382ffc836af85f",
"level": "admin",
"name": "DataAdmin",
"type": "default"
},
{
"id": "63580b8d5cf9728f19217be0",
"level": "user",
"name": "PrivateAnalyticsContentCreator",
"type": "default"
},
{
"id": "6356f0425cf9728f1962b942",
"level": "user",
"name": "DataServicesContributor",
"type": "default"
}
],
"created": "2020-05-18T09:38:29.214Z",
"createdAt": "2020-05-18T09:38:29.214Z",
"email": "martina.testoni@dkdaklaldkdaklladaaddddl.com",
"id": "USERID1",
"lastUpdated": "2023-04-04T07:32:00.756Z",
"lastUpdatedAt": "2023-04-04T07:32:00.756Z",
"name": "Martina Testoni",
"picture": "https://s.gravatar.com/avatar/gravatarimage=pg\u0026d=https%3A%2F%2Fcdn.auth0.com%2Favatars%2Fdp.png",
"preferredLocale": "",
"preferredZoneinfo": "Europe/Copenhagen",
"roles": [
"Developer",
"TenantAdmin",
"SharedSpaceCreator",
"ManagedSpaceCreator",
"DataSpaceCreator",
"AnalyticsAdmin",
"DataAdmin",
"PrivateAnalyticsContentCreator",
"DataServicesContributor"
],
"status": "active",
"subject": "auth0|SUBJECTID2",
"tenantId": "TENANTID"
},
{
"assignedGroups": [],
"assignedRoles": [
{
"id": "608050f7634644db3678b17f",
"level": "admin",
"name": "TenantAdmin",
"type": "default"
},
{
"id": "605a1c2151382ffc836af86b",
"level": "user",
"name": "DataSpaceCreator",
"type": "default"
},
{
"id": "608050f7634644db3678b1a2",
"level": "user",
"name": "Developer",
"type": "default"
},
{
"id": "605a1c2151382ffc836af866",
"level": "user",
"name": "ManagedSpaceCreator",
"type": "default"
},
{
"id": "63580b8d5cf9728f19217be0",
"level": "user",
"name": "PrivateAnalyticsContentCreator",
"type": "default"
},
{
"id": "605a1c2151382ffc836af862",
"level": "user",
"name": "SharedSpaceCreator",
"type": "default"
},
{
"id": "6356f0425cf9728f1962b95c",
"level": "user",
"name": "Steward",
"type": "default"
},
{
"id": "605a1c2151382ffc836af85d",
"level": "admin",
"name": "AnalyticsAdmin",
"type": "default"
},
{
"id": "62bb165356d1879582c1b468",
"level": "admin",
"name": "AuditAdmin",
"type": "default"
},
{
"id": "605a1c2151382ffc836af85f",
"level": "admin",
"name": "DataAdmin",
"type": "default"
}
],
"created": "2023-03-31T08:44:37.332Z",
"createdAt": "2023-03-31T08:44:37.332Z",
"email": "Gentile.Faccenda@dkdaklaldkdaklladaaddddl.com",
"id": "USERID2",
"lastUpdated": "2023-04-03T11:24:35.037Z",
"lastUpdatedAt": "2023-04-03T11:24:35.037Z",
"name": "Gentile Faccenda",
"picture": "https://s.gravatar.com/avatar/randomurl=https%3A%2F%2Fcdn.auth0.com%2Favatars%2Fdp.png",
"roles": [
"TenantAdmin",
"DataSpaceCreator",
"Developer",
"ManagedSpaceCreator",
"PrivateAnalyticsContentCreator",
"SharedSpaceCreator",
"Steward",
"AnalyticsAdmin",
"AuditAdmin",
"DataAdmin"
],
"status": "active",
"subject": "auth0|IDPSUBJECT2",
"tenantId": "TENANTID"
}
]
qlik user ls --limit 1000 | ConvertFrom-Json | ConvertTo-Csv > tenantusers.csv
This article explains how to import and export master items to and from a Qlik Sense app using the Microsoft Excel connector in Qlik Application Automation.
Content:
The first part of this article will explain how to export all of your master items configured in your Qlik Sense App to a Microsoft Excel sheet. The second part will explain how to import those master items from the Microsoft Excel sheet back to a Qlik Sense App.
For this, you will need a Qlik Sense app in your tenant that contains measures, dimensions, and variables you want to export. You'll also need an empty Microsoft Excel file. The image below contains a basic example on exporting master items.
The following steps will guide you through recreating the above automation:
An export of the above automation can be found at the end of this article as Export master items to a Microsoft Excel sheet.json
For this example, you'll first need a Microsoft Excel file with sheets configured for each master item type (dimensions, measures, and variables). Use the above example to generate this file. The image below contains a basic example on importing master items from Microsoft Excel to a Qlik Sense app.
An export of the above automation can be found at the end of this article as Import master items from a Microsoft Excel Sheet.json
Follow the same steps to build automations that import/export dimensions and variables.
Let's go over some edge cases when exporting information to Microsoft Excel:
Please check the following articles for more information about working with master items in Qlik Application Automation and also uploading data to Microsoft Excel.
Follow the steps provided in this article How to import & export automations to import the automation from the shared JSON file.
The information in this article is provided as-is and to be used at own discretion. Depending on tool(s) used, customization(s), and/or other factors ongoing support on the solution below may not be provided by Qlik Support.
Using the change-owner REST API call for app objects or the qlik-cli app object change-owner command results in:
403 - Forbidden (empty response)
This is a current limitation. As specified on the API call information page, the user running the call must be the owner of the object. Even tenant admins won't be able to run the call, if they are not the object's current owners.
As the qlik-cli command uses the same API call, the behaviour is identical.
The user running the call/command is not the object owner.