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Model Jira Data Using Azure Analysis Services
Leverage CData Connect Cloud to establish a connection between Azure Analysis Services and Jira, enabling the direct import of real-time Jira data.
Microsoft Azure Analysis Services (AAS) is a fully-managed platform-as-a-service (PaaS) offering that delivers enterprise-grade data models in the cloud. When combined with CData Connect Cloud, AAS facilitates immediate cloud-to-cloud access to Jira data for applications. This article outlines the process of connecting to Jira via Connect Cloud and importing Jira data into Visual Studio using an AAS extension.
CData Connect Cloud offers a seamless cloud-to-cloud interface tailored for Jira, enabling you to create live models of Jira data in Azure Analysis Services without the need to replicate data to a natively supported database. While constructing high-quality semantic data models for business reports and client applications, Azure Analysis Services formulates SQL queries to retrieve data. CData Connect Cloud is equipped with optimized data processing capabilities right from the start, directing all supported SQL operations, including filters and JOINs, directly to Jira. This leverages server-side processing for swift retrieval of the requested Jira data.
About Jira Data Integration
CData simplifies access and integration of live Jira data. Our customers leverage CData connectivity to:
- Gain bi-directional access to their Jira objects like issues, projects, and workflows.
- Use SQL stored procedures to perform functional actions like changing issues status, creating custom fields, download or uploading an attachment, modifying or retrieving time tracking settings, and more.
- Authenticate securely using a variety of methods, including username and password, OAuth, personal access token, API token, Crowd or OKTA SSO, LDAP, and more.
Most users leverage CData solutions to integrate Jira data with their database or data warehouse, whether that's using CData Sync directly or relying on CData's compatibility with platforms like SSIS or Azure Data Factory. Others are looking to get analytics and reporting on live Jira data from preferred analytics tools like Tableau and Power BI.
Learn more about how customers are seamlessly connecting to their Jira data to solve business problems from our blog: Drivers in Focus: Collaboration Tools.
Getting Started
Prerequisites
Before you connect, you must first do the following:
- Connect a data source to your CData Connect Cloud account. Detailed steps are provided in the next section.
- Generate a Personal Access Token (PAT). Copy this down, as it acts as your password during authentication.
- Create a server in Azure Analysis Services to which you will deploy your data from CData Connect Cloud.
- Install and configure an On-Premise Gateway in your system. This will pull data from the source via CData Connect Cloud into the Azure Analysis Services project and deploy models to the server. Refer to the given link to find the detailed process.
Configure Jira Connectivity for AAS
Connectivity to Jira from Azure Analysis Services is made possible through CData Connect Cloud. To work with Jira data from Azure Analysis Services, we start by creating and configuring a Jira connection.
- Log into Connect Cloud, click Sources, and then click Add Connection
- Select "Jira" from the Add Connection panel
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Enter the necessary authentication properties to connect to Jira.
To connect to JIRA, provide the User and Password. Additionally, provide the Url; for example, https://yoursitename.atlassian.net.
- Click Create & Test
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Navigate to the Permissions tab in the Add Jira Connection page and update the User-based permissions.
Add a Personal Access Token
When connecting to Connect Cloud through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect Cloud. It is best practice to create a separate PAT for each service to maintain granularity of access.
- Click on the Gear icon () at the top right of the Connect Cloud app to open the settings page.
- On the Settings page, go to the Access Tokens section and click Create PAT.
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Give the PAT a name and click Create.
- The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.
With the connection configured and a PAT generated, you are ready to connect to Jira data from Visual Studio using Azure Analysis Services.
Connect to Jira in Visual Studio Using AAS
The steps below outline connecting to CData Connect Cloud from Azure Analysis Services to create a new Jira data source. You will need the Microsoft Analysis Services Project extension installed in Microsoft Visual Studio to continue.
- In Visual Studio, create a new project. Select Analysis Services Tabular Project. Click on Next.
- In the Configure your new project dialog box, enter a name for your project in the Project name field. Fill in the rest of the fields.
- Click on Create. The Tabular model designer dialog box opens. Select Workspace server and enter the address of your Azure Analysis Services server (for example, asazure://eastus.azure.windows.net/myAzureServer). Also, make sure to select the option SQL Server 2022 / Azure Analysis Services (1600) from the Compatibility level dropdown. Click on Test Connection to check if the connection details are correct. Click OK and sign in to your server.
- Now, click on OK to create the project. Your Visual Studio window should resemble the following screenshot:
- In the Tabular Model Explorer window of Visual Studio, right-click Data Sources and select Import From Data Source.
- In the Get Data window, select SQL Server database and click Connect. In the Server field, enter the Virtual SQL Server endpoint and the port separated by a comma: e.g., “tds.cdata.com, 14333”, and click on OK.
- Click on Database and enter the following information:
- User name: Enter your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud interface. For example, [email protected].
- Password: Enter the PAT you generated on the Settings page.
Click on Connect. If successful, the Navigator window will pop up.
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In the Navigator window, search and select the tables of your choice
- You should now see the Salesforce table populated with data in the preview section on the right panel.
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Click on Load to import the data.
Now that you have imported the Jira data into your data model, you are ready to deploy the project to Azure Analysis Services for use in business reports, client applications, and more.
Get CData Connect Cloud
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