Wootric provides tools businesses use to monitor and improve customer happiness through the use of Net Promoter Score (NPS), CSAT, and Customer Effort Score metrics.

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.

Wootric provides a REST API that lets you get information about users and segments, responses, metrics, and other elements. If, for example, you wanted to retrieve a list of all end users, you could call GET /v1/end_users. This API call takes five optional parameters that let you filter and limit the results returned.

The Wootric API returns data in JSON format. For example, the result of a call to retrieve a list of end users might look like this.

[
  {
    "id": 1,
    "created_at" : "2017-12-01 18:36:59",
    "updated_at" : "2017-12-01 18:36:59",
    "email": "nps@example.com",
    "last_surveyed": null,
    "external_created_at": null,
    "user_id": 16,
    "page_views_count" : 1,
    "properties": {"plan": "Small Business", "product": "Example"}
  },
  {
    "id": 2,
    "created_at" : "2017-12-01 18:36:59",
    "updated_at" : "2017-12-04 12:43:44",
    "email": "nps2@example.com",
    "last_surveyed": null,
    "external_created_at": null,
    "user_id": 16,
    "page_views_count" : 3,
    "properties": {"plan": "Enterprise", "product": "The Company"}
  }
]

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. Wootric'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 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.

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.

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 Wootric.

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