Harvest to Google Data Studio

This page provides you with instructions on how to extract data from Harvest and analyze it in Google Data Studio. (If the mechanics of extracting data from Harvest 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 Harvest?

Harvest provides web-based time and expense tracking software as a service, along with a visual reporting dashboard. In addition to a browser-based interface, it offers apps for Android and iPhone, and a native MacOS desktop app.

Getting data out of Harvest

Harvest supports a REST API that lets developers access data in a Harvest account programmatically. You can access data on timesheets, invoices, expenses, and estimates, among other things. For example, to list all time entries, you could call GET /v2/time_entries. You can incorporate any of 10 parameters into that call to limit the data returned to a specified user, client, timeframe, or other criteria.

Sample Harvest data

The Harvest API returns JSON-format data. For instance, the result of a call for time entries might return data like this:

{
  "time_entries":[
    {
      "id":636709355,
      "spent_date":"2017-03-02",
      "user":{
        "id":1782959,
        "name":"Kim Allen"
      },
      "client":{
        "id":5735774,
        "name":"ABC Corp"
      },
      "project":{
        "id":14307913,
        "name":"Marketing Website"
      },
      "task":{
        "id":8083365,
        "name":"Graphic Design"
      },
      "user_assignment":{
        "id":125068553,
        "is_project_manager":true,
        "is_active":true,
        "budget":null,
        "created_at":"2017-06-26T22:32:52Z",
        "updated_at":"2017-06-26T22:32:52Z",
        "hourly_rate":100.0
      },
      "task_assignment":{
        "id":155502709,
        "billable":true,
        "is_active":true,
        "created_at":"2017-06-26T21:36:23Z",
        "updated_at":"2017-06-26T21:36:23Z",
        "hourly_rate":100.0,
        "budget":null
      },
      "hours":2.0,
      "notes":"Adding CSS styling",
      "created_at":"2017-06-27T15:50:15Z",
      "updated_at":"2017-06-27T16:47:14Z",
      "is_locked":true,
      "locked_reason":"Item Approved and Locked for this Time Period",
      "is_closed":true,
      "is_billed":false,
      "timer_started_at":null,
      "started_time":"3:00pm",
      "ended_time":"5:00pm",
      "is_running":false,
      "invoice":null,
      "external_reference":null,
      "billable":true,
      "budgeted":true,
      "billable_rate":100.0,
      "cost_rate":50.0
    },
    {
      "id":636708723,
      "spent_date":"2017-03-01",
      "user":{
        "id":1782959,
        "name":"Kim Allen"
      },
      "client":{
        "id":5735776,
        "name":"123 Industries"
      },
      "project":{
        "id":14308069,
        "name":"Online Store - Phase 1"
      },
      "task":{
        "id":8083366,
        "name":"Programming"
      },
      "user_assignment":{
        "id":125068554,
        "is_project_manager":true,
        "is_active":true,
        "budget":null,
        "created_at":"2017-06-26T22:32:52Z",
        "updated_at":"2017-06-26T22:32:52Z",
        "hourly_rate":100.0
      },
      "task_assignment":{
        "id":155505014,
        "billable":true,
        "is_active":true,
        "created_at":"2017-06-26T21:52:18Z",
        "updated_at":"2017-06-26T21:52:18Z",
        "hourly_rate":100.0,
        "budget":null
      },
      "hours":1.0,
      "notes":"Importing products",
      "created_at":"2017-06-27T15:49:28Z",
      "updated_at":"2017-06-27T16:47:14Z",
      "is_locked":true,
      "locked_reason":"Item Invoiced and Approved and Locked for this Time Period",
      "is_closed":true,
      "is_billed":true,
      "timer_started_at":null,
      "started_time":"1:00pm",
      "ended_time":"2:00pm",
      "is_running":false,
      "invoice":{
        "id":13150403,
        "number":"1001"
      },
      "external_reference":null,
      "billable":true,
      "budgeted":true,
      "billable_rate":100.0,
      "cost_rate":50.0
    },
    {
      "id":636708574,
      "spent_date":"2017-03-01",
      "user":{
        "id":1782959,
        "name":"Kim Allen"
      },
      "client":{
        "id":5735776,
        "name":"123 Industries"
      },
      "project":{
        "id":14308069,
        "name":"Online Store - Phase 1"
      },
      "task":{
        "id":8083369,
        "name":"Research"
      },
      "user_assignment":{
        "id":125068554,
        "is_project_manager":true,
        "is_active":true,
        "budget":null,
        "created_at":"2017-06-26T22:32:52Z",
        "updated_at":"2017-06-26T22:32:52Z",
        "hourly_rate":100.0
      },
      "task_assignment":{
        "id":155505016,
        "billable":false,
        "is_active":true,
        "created_at":"2017-06-26T21:52:18Z",
        "updated_at":"2017-06-26T21:54:06Z",
        "hourly_rate":100.0,
        "budget":null
      },
      "hours":1.0,
      "notes":"Evaluating 3rd party libraries",
      "created_at":"2017-06-27T15:49:17Z",
      "updated_at":"2017-06-27T16:47:14Z",
      "is_locked":true,
      "locked_reason":"Item Approved and Locked for this Time Period",
      "is_closed":true,
      "is_billed":false,
      "timer_started_at":null,
      "started_time":"11:00am",
      "ended_time":"12:00pm",
      "is_running":false,
      "invoice":null,
      "external_reference":null,
      "billable":false,
      "budgeted":true,
      "billable_rate":null,
      "cost_rate":50.0
    },
    {
      "id":636707831,
      "spent_date":"2017-03-01",
      "user":{
        "id":1782959,
        "name":"Kim Allen"
      },
      "client":{
        "id":5735776,
        "name":"123 Industries"
      },
      "project":{
        "id":14308069,
        "name":"Online Store - Phase 1"
      },
      "task":{
        "id":8083368,
        "name":"Project Management"
      },
      "user_assignment":{
        "id":125068554,
        "is_project_manager":true,
        "is_active":true,
        "budget":null,
        "created_at":"2017-06-26T22:32:52Z",
        "updated_at":"2017-06-26T22:32:52Z",
        "hourly_rate":100.0
      },
      "task_assignment":{
        "id":155505015,
        "billable":true,
        "is_active":true,
        "created_at":"2017-06-26T21:52:18Z",
        "updated_at":"2017-06-26T21:52:18Z",
        "hourly_rate":100.0,
        "budget":null
      },
      "hours":2.0,
      "notes":"Planning meetings",
      "created_at":"2017-06-27T15:48:24Z",
      "updated_at":"2017-06-27T16:47:14Z",
      "is_locked":true,
      "locked_reason":"Item Invoiced and Approved and Locked for this Time Period",
      "is_closed":true,
      "is_billed":true,
      "timer_started_at":null,
      "started_time":"9:00am",
      "ended_time":"11:00am",
      "is_running":false,
      "invoice":{
        "id":13150403,
        "number":"1001"
      },
      "external_reference":null,
      "billable":true,
      "budgeted":true,
      "billable_rate":100.0,
      "cost_rate":50.0
    }
  ],
  "per_page":100,
  "total_pages":1,
  "total_entries":4,
  "next_page":null,
  "previous_page":null,
  "page":1,
  "links":{
    "first":"https://api.harvestapp.com/v2/time_entries?page=1&per_page=100",
    "next":null,
    "previous":null,
    "last":"https://api.harvestapp.com/v2/time_entries?page=1&per_page=100"
  }
}

Preparing Harvest data

If you don't already have a data structure in which to store the data you retrieve, you'll have to create a schema for your data tables. Then, for each value in the response, you'll need to identify a predefined datatype (INTEGER, DATETIME, etc.) and build a table that can receive them. Harvest's API documentation should tell you what fields are provided by each endpoint, along with their corresponding datatypes.

Complicating things is the fact that the records retrieved from the source may not always be "flat" – some of the objects may actually be lists. This means you'll likely have to create additional tables to capture the unpredictable cardinality in each record.

Keeping Harvest data up to date

At this point you've coded up a script or written a program to get the data you want and successfully moved it into your data warehouse. But how will you load new or updated data? It's not a good idea to replicate all of your data each time you have updated records. That process would be painfully slow and resource-intensive.

Instead, identify key fields that your script can use to bookmark its progression through the data and use to pick up where it left off as it looks for updated data. Auto-incrementing fields such as updated_at or created_at work best for this. When you've built in this functionality, you can set up your script as a cron job or continuous loop to get new data as it appears in Harvest.

And remember, as with any code, once you write it, you have to maintain it. If Harvest modifies its API, or the API sends a field with a datatype your code doesn't recognize, you may have to modify the script. If your users want slightly different information, you definitely will have to.

From Harvest to your data warehouse: An easier solution

As mentioned earlier, the best practice for analyzing Harvest data in Google Data Studio 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 Harvest to Redshift, Harvest to BigQuery, and Harvest to Snowflake.

Easier yet, however, is using a solution that does all that work for you. Products like Stitch were built to solve this problem automatically. With just a few clicks, Stitch starts extracting your Harvest data via the API, structuring it in a way that is optimized for analysis, and inserting that data into a data warehouse that can be easily accessed and analyzed by Google Data Studio.