Calculated fields may appear to be a simple feature to add to any user interface, even an analytics dashboard. In fact, Google first added calculated fields to Google Analytics reports a few years ago. But a recent calculated fields update that Google added to Google Data Studio signifies how such features are simplifying data exploration and visualization tasks.
First, what are calculated fields? According to Google, “a calculated field is a formula that performs some action on one or more other fields in your data source.” Calculated fields can perform mathematical equations or manipulate text and other parameters, such as dates and geographic information. The values derived from those actions can then be displayed in charts.
Google Data Studio offers two kinds of calculated fields: those that are created in the data source and, a new feature, those created within charts in reports.
Calculated Fields: The Benefits
Each version has specific benefits. The primary benefit of inserting calculated fields into charts is to quickly and easily add fields without having to access the data source.
When you create calculated fields in data sources, which was the only option with previous versions of Data Studio, you had to have access to the data source in order to visually display the calculated values in charts and other graphics.
With the new chart-specific calculated fields, you don’t need to access the data source to add calculated fields to charts.
You can also use blended data (data from more than one source) as a variable in the calculations carried out by chart-specific calculated fields. You can’t do that with data source calculated fields.
The ability to use blended data is helpful when conducting an exploratory data analysis (EDA). For example, you could use data from different sources to create a calculated field that multiplied the number of website visits by a target cost per click to get a budget projection. The data on the number of visits could come from an analytics tool, and cost-per-click data could come from a digital ad platform.
Related Article: Google Data Studio Makes Dynamic Report Building Easy
What Calculated Fields Mean to BI Analysts
Calculated fields are useful for ad campaign spending and budget calculations. But a potential deeper benefit for business intelligence analysts lies within another Data Studio feature — connectors that link data sources to Data Studio graphs. While connectors have long existed for principle Google platforms like Google Ads and BigQuery, developers are starting to launch connectors for third-party databases.
That means you could use connectors to import data for Google Data Studio calculated fields that use blended data. With connectors, you could do side-by-side comparisons of calculated field values derived from different sources. In the budget example cited earlier, for instance, you could run the calculation multiple times using traffic data from a different source each time and then display the results in a chart, allowing the analysts to quickly compare the various projections.
More User-Friendly Data Visualization Updates
Recently, providers of data storage systems have introduced user-friendly access features so that data fields can be adjusted in real time. These updates are part of an industry movement to reduce the time it takes to conduct EDAs.
Many of the updates are in open-source platforms. For example, MongoDB just introduced Charts to allow easier visualization of data collections. Some have long been available, such as Shiny, an open-source R package designed to make it easy to build interactive web apps in R. With Shiny, you can create graphs that can be seen and adjusted in a browser, leveraging HTML and CSS elements to create a interactive charts that adjust according to user-selected data sets.
Calculated fields can help you visualize how data columns can be called in a calculation, and how that activity impacts the graphs Data Studio creates. Moreover, creating calculated fields with connected data can spark new ideas in managing the varieties of data types that typically appear in a data source.
Analysts should pay close attention to the latest updates in data tools. A seemingly simple feature like calculated fields in Google Data Studio can save time and effort.