Connect Jira to Tableau

To connect Jira to Tableau and further import data, follow the step-by-step guide below:

Step 1: Collect data
First, connect your Jira account. Next, you can adjust the optional settings. For instance, you will be offered the option to specify a Jira Cloud instance with data you would like to export, choose particular columns to load, and others.



As soon as you finish with the source settings, proceed to the transformations step.

Step 2: Organize & Transform
Before importing Jira to Tableau, you can preview your data to check whether it is accurate. If there is something you would like to change, consider making the following adjustments:

• Edit, rearrange, hide, or add columns.
• Apply various filters and sort your data.
• Create new columns with custom formulas.
• Combine data from multiple accounts or apps.

By transforming the data like this, you will ensure that your report is structured in accordance with your specific analytics requirements.



When you make sure that data meets your expectations, move to the destination settings.

Step 3: Load & Automate
Generate a link to the integration URL. Then, set up a schedule for automated refreshes and run the importer. To finally transfer your data from Jira to Tableau, follow the connector setup instructions to complete the connection.

To maintain your Tableau report in line with the latest changes to the source data, you must enable automated refreshes. This capability allows your report to update automatically without needing manual input. You can set the frequency to your liking, choosing from options like monthly, daily, hourly, or even as frequently as every 30 or 15 minutes.

Moreover, you can select the specific days of the week, the desired time slot, and the applicable time zone.



Thanks to auto-refreshes configured at preferred intervals, your report will always be supplied with the most recent data.

Coupler.io offers various import modes tailored to fetch data from multiple sources.

To take advantage of this functionality, simply click the corresponding button to start connecting other applications when adjusting the source settings. Then, you'll proceed through a process much the same as setting up your initial data source.

Coupler.io supports integration with a wide range of apps or different accounts of the same one without creating additional importers.

Furthermore, the data exported from multiple sources can be merged into a single dataset. Using this opportunity, you can combine Excel data with relevant records from other platforms.

Once you've added the needed sources and reached the transformation step, you can unite your data in two ways:

• Append: Blend data from one source into another, provided they share identical column names.
• Join: Merge your datasets side-by-side with at least one matching column name.

Through the integration of diverse sources, you can analyze larger data amounts at the same time. This way, you ensure a multifaceted interpretation of your data.

Apart from the option to connect Jira to Tableau, Coupler.io makes it possible for you to replicate data importers. This way, you can load your data into a wide variety of alternative destinations:

• Spreadsheet applications: – Microsoft Excel and Google Sheets – these apps will help you create reports on your data in a quick and simple manner.
• Data warehousing software: – BigQuery, PostgreSQL, or Redshift – send your Jira records here if you'd like to store, query, and perform complex analysis of those.
• Other business intelligence (BI) tools – Data Studio, Power BI, and Qlik Sense – to benefit from visual analytics: transform data into interactive dashboards, make it easily understandable, as well as spot trends and patterns in it.

When it comes to importing Jira data into these applications, this is very similar to loading it into Tableau, as previously demonstrated.