Front to Power BI

This page provides you with instructions on how to extract data from Front and analyze it in Power BI. (If the mechanics of extracting data from Front seem too complex or difficult to maintain, check out Stitch, which can do all the heavy lifting for you in just a few clicks.)

What is Front?

Front lets you manage all of your communication channels – email, social media, chat, SMS – in one place, and helps your team collaborate around messages. You can comment on email threads within shared inboxes like support@yourcompany.com without those comments being visible to the sender, and without having to forward or reply-all. You can assign emails to individuals, and set reminders to respond later. Front also offers email templates, sequences, mail merge, and shortcuts to automate your workflow.

What is Power BI?

Power BI is Microsoft’s business intelligence offering. It's a powerful platform that includes capabilities for data modeling, visualization, dashboarding, and collaboration. Many enterprises that use Microsoft's other products can get easy access to Power BI and choose it for its convenience, security, and power.

With high-value use cases across analysts, IT, business users, and developers, Power BI offers a comprehensive set of functionality that has consistently landed Microsoft in Gartner's "Leaders" quadrant for Business Intelligence.

Getting data out of Front

You can use Front's API to get data about teams, conversations, and many more tables. For example, to get information about a team, you could GET https://api2.frontapp.com/teams/{team_id}.

Sample Front data

Here's an example of the kind of response you might see when querying a team.

{
  "_links": {
    "self": "https://api2.frontapp.com/teams/tim_55c8c149"
  },
  "id": "tim_55c8c149",
  "name": "Delivery",
  "inboxes": [
    {
      "_links": {
        "self": "https://api2.frontapp.com/inboxes/inb_55c8c149",
        "related": {
          "teammates": "https://api2.frontapp.com/inboxes/inb_55c8c149/teammates",
          "conversations": "https://api2.frontapp.com/inboxes/inb_55c8c149/conversations",
          "channels": "https://api2.frontapp.com/inboxes/inb_55c8c149/channels",
          "owner": "https://api2.frontapp.com/teams/tim_55c8c149"
        }
      },
      "id": "inb_55c8c149",
      "name": "Team",
      "is_private": false
    }
  ],
  "members": [
    {
      "_links": {
        "self": "https://api2.frontapp.com/teammates/tea_55c8c149",
        "related": {
          "inboxes": "https://api2.frontapp.com/teammates/tea_55c8c149/inboxes",
          "conversations": "https://api2.frontapp.com/teammates/tea_55c8c149/conversations"
        }
      },
      "id": "tea_55c8c149",
      "email": "leela@planet-express.com",
      "username": "leela",
      "first_name": "Leela",
      "last_name": "Turanga",
      "is_admin": true,
      "is_available": true,
      "is_blocked": false
    }
  ]
}

Loading data into Power BI

You can analyze any data in Power BI, as long as that data exists in a data warehouse that's connected to your Power BI account. The most common data warehouses include Amazon Redshift, Google BigQuery, and Snowflake. Microsoft also has its own data warehousing platform called Azure SQL Data Warehouse.

Connecting these data warehouses to Power BI is relatively simple. The Get Data menu in the Power BI interface allows you to import data from a number of sources, including static files and data warehouses. You'll find each of the warehouses mentioned above among the options in the Database list. The Power BI documentation provides more details on each.

Analyzing data in Power BI

In Power BI, each table in the data warehouse you connect is known as a dataset, and the analyses conducted on these datasets are known as reports. To create a report, use Power BI’s report editor, a visual interface for building and editing reports.

The report editor guides you through several selections in the course of building a report: the visualization type, fields being used in the report, filters being applied, any formatting you wish to apply, and additional analytics you may wish to layer onto your report, such as trendlines or averages. You can explore all of the features related to analyzing and tracking data in the Power BI documentation.

Once you've created a report, Power BI lets you share it with report "consumers" in your organization.

Keeping Front data up to date

Now what? You've built a script that pulls data from Front and loads it into your data warehouse, but what happens tomorrow when you have new transactions?

The key is to build your script in such a way that it can identify incremental updates to your data. Thankfully, many of Front's API results include fields like created_at that allow you to identify records that are new since your last update (or since the newest record you've copied). Once you've take new data into account, you can set your script up as a cron job or continuous loop to keep pulling down new data as it appears.

From Front to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Front data in Power BI is to store that data inside a data warehousing platform alongside data from your other databases and third-party sources. You can find instructions for doing these extractions for leading warehouses on our sister sites Front to Redshift, Front to BigQuery, Front to Azure SQL Data Warehouse, Front to PostgreSQL, Front to Panoply, and Front to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to move data from Front to Power BI automatically. With just a few clicks, Stitch starts extracting your Front data via the API, structuring it in a way that's optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Power BI.