SAP Analytics Cloud dashboard templates supported with pre-configured data sources are now available in this latest version. We are happy to offer you the new and exciting SAC Jira reporting experience!
Build your first SAC dashboard in a day with Jira SAP Analytics Cloud dashboard templates in SAP Analytics Cloud for Jira from Alpha Serve!
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SAP Analytics Cloud Templates Description
Jira Timework Report
Jira Timework Report is a detailed dashboard designed to provide valuable insights into work logs across all or specific projects in your Jira Cloud instance. It displays critical KPIs for the selected projects, making it a vital asset for project managers.
The report allows users to monitor the time spent on different tasks, track project progress, and manage resource allocation effectively. With the SAP Analytics Cloud Connector for Jira, users don't need to build a comprehensive work log report from scratch. Instead, they can construct an insightful Jira Timework Report in SAP Analytics Cloud in minutes, simplifying the entire process.
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Jira Sprint Dashboard
Jira Sprint Dashboard is an indispensable report designed with Scrum Masters and Agile Coaches in mind. This interactive dashboard offers an in-depth view of sprint performance, enabling users to track progress, measure team velocity, and pinpoint areas for improvement.The dashboard is a vital resource for agile project management, providing insights that can bolster team productivity. The connector's pre-built template simplifies the creation of a dashboard that can encompass multiple ongoing sprints within the SAP Analytics Cloud. This means users can more quickly focus on performance review and improvement initiatives.
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How to Use SAP Analytics Cloud Dashboard Templates
Go to the Templates tab.
2. Select the template you would like to use and click either on its name or the Create Data Source button.
3. Set up the auto-generated data source. You can edit the data source name, add a description and apply a project filter. Click Next.
4. Copy the generated data source link and click the Next button to download the package file.
How to Import SAC Templates into SAP Analytics Cloud?
In SAP Analytics Cloud, go to Transport > Export > My Content.
In the opened window, select Upload > Select Package and select the package you’ve downloaded from Alpha Serve. Press OK.
Select Create data source in front of the desired dashboard template.
In the Name* field, enter the data source name.
[Optional] In the Description field, enter the data source description.
[Optional] Apply filter by Projects.
Select Next.
Copy the generated URL, and then select Next.
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After selecting Next, the selected dashboard template as a .package file will be downloaded to your computer. |
Open your SAP Analytics Cloud, and then navigate to Transport.
Select Export, and then select My Content.
Select (1) Upload, and then select (2) Select Package.
Upload the .package file you've downloaded before, and then select OK.
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It takes SAP Analytics about a minute to upload the package. |
Select Refresh to see the uploaded resource. |
Return to Transport
, then Import, and then select Content Network Storage
.
Select the dashboard template file you’ve just uploaded.
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In our case, it’s Jira Sprint Dashboard. |
Select the import option that suits your needs, and then select Import.
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It’s recommended to review the impacted content, analyze and decide what’s better - overwriting the objects & data or not. In our case, we selected to overwrite objects and data. |
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The import process will be shown in the notification bar. |
Once the import is |
done, |
a pop-up notification |
will appear. |
Select the notification, and then select the connection
Enter the URL you’ve copied from the SAP Analytics Cloud Connector for Jira, your email, and the Access Token.
After that, go to Modeler and find the model you need (in our case, it’s Sprint Dashboard) in the Recent files or using Search.
.
In the *Connection Name field, enter the name for this connection.
In the *Data Service URL field, enter the copied URL in step 7.
In the *Authentication Type field, select Basic Authentication.
In the *User Name field, enter the username associated with your Jira cloud account.
In the *Password field, enter your token created here.
Select OK.
Navigate to Modeler, find the model you need, and then open it.
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In our case, it's Sprint Dashboard. The model might be in Recent files or try using Search. |
In the Workspace section, select Data Management.
Select the Import Job and press Refresh.
Under Import Jobs, select the corresponding job, and then select Refresh.
Data can’t be refreshed if there are any empty tables. You’ll see
the following message in this case: The data query returns an empty result
set.
Open the dashboard
, go to Stories
, and then select Recent Files
.
Find your dashboard.
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Congratulations! Now you can view your dashboard. |
SAP Analytics Cloud Templates Overview
Jira Timework Report
The Jira Timework Report Dashboard Template provides a succinct snapshot of workloads according to users and selected Jira projects. It presents a detailed view of time spent on each project day by day, enhancing project management capabilities. A significant aspect of this template is its ability to clearly communicate complex data through intuitive and visually engaging SAP Analytics Cloud charts and graphs. It brings clarity to tracking, revealing both high-level overviews and granular details of time utilization across Jira projects.
Jira Sprint Dashboard
The Jira Sprint Dashboard Template for SAP Analytics Cloud offers a comprehensive overview of sprint activities. It allows the selection of sprints for focused analysis and provides a mechanism to filter sprints based on their start and end dates. One of its key features is a detailed tracking tool that exhibits the number of tasks completed alongside original and remaining estimates. This information can be viewed at task and user levels, facilitating workload management and productivity monitoring. Furthermore, the dashboard .
classifies and enumerates the issues encountered during the sprint, offering insights into recurring problems and their impact on the project timeline. Time spent on each issue is broken down, providing a window into the team's problem-solving efficiency and helping managers make choices based on reliable data, leading to improved workflow management.