Freshdesk provides cloud-based customer support software for help desk staff.

Apache Superset is a cloud-native data exploration and visualization platform that businesses can use to create business intelligence reports and dashboards. It includes a state-of-the-art SQL IDE, and it's open source software, free of cost. The platform was originally developed at Airbnb and donated to the Apache Software Foundation.

Freshdesk provides a REST API that lets you get data on tickets, agents, companies, and other information out of the service's back end. Some of the API calls are simple; for example, to list all tickets, you could call GET /api/v2/tickets. You can use optional filters (such as company ID and updated since date/time) in the GET request to limit the data you retrieve, and the optional include parameter to retrieve fields that the API doesn't send by default.

Freshdesk returns information in JSON format. Each JSON object may contain more than a dozen attributes, which you have to parse before loading the data into your data warehouse. Here's an example of what some of the data for that call to return all tickets might look like:

[
  {
    "cc_emails" : ["user@cc.com", "user2@cc.com"],
    "fwd_emails" : [ ],
    "reply_cc_emails" : ["user@cc.com", "user2@cc.com"],
    "fr_escalated" : false,
    "spam" : false,
    "email_config_id" : null,
    "group_id" : 2,
    "priority" : 1,
    "requester_id" : 5,
    "responder_id" : 1,
    "source" : 2,
    "status" : 2,
    "subject" : "Please help",
    "to_emails" : null,
    "product_id" : null,
    "id" : 18,
    "type" : Lead,
    "created_at" : "2017-11-17T12:02:50Z",
    "updated_at" : "2017-11-17T12:02:51Z",
    "due_by" : "2017-11-20T11:30:00Z",
    "fr_due_by" : "2017-11-18T11:30:00Z",
    "is_escalated" : false,
    "description_text" : "Computer is not working as expected",
    "description" : "Computer is not working as expected",
    "custom_fields" : {
      "category" : "Default"
    }
  },
  {
    "cc_emails" : [ ],
    "fwd_emails" : [ ],
    "reply_cc_emails" : [ ],
    "fr_escalated" : false,
    "spam" : false,
    "email_config_id" : null,
    "group_id" : null,
    "priority" : 1,
    "requester_id" : 1,
    "responder_id" : null,
    "source" : 2,
    "status" : 2,
    "subject" : "",
    "to_emails" : null,
    "product_id" : null,
    "id" : 17,
    "type" : null,
    "created_at" : "2017-11-17T12:02:06Z",
    "updated_at" : "2017-11-17T12:02:07Z",
    "due_by" : "2017-11-20T11:30:00Z",
    "fr_due_by" : "2017-11-18T11:30:00Z",
    "is_escalated" : false,
    "description_text" : "Not given.",
    "description" : "
Not given.
",
    "custom_fields" : {
      "category" : null
    }
  }
]

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. Freshdesk's 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.

You must replicate data from your SaaS applications to a data warehouse before you can report on it using Superset. Superset can connect to almost 30 databases and data warehouses. Once you choose a data source you want to connect to, you must specify a host name and port, database name, and username and password to get access to the data. You then specify the database schema or tables you want to work with.

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 Freshdesk.

And remember, as with any code, once you write it, you have to maintain it. If Freshdesk 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.