Looker Studio Features, Beyond Basics

In the previous three chapters of this book, you have learned about how to get started with Looker Studio and explored its major entities. You understood how to use the many fundamental features of the tool to build effective data visualizations and reports. This chapter explores some additional capabilities that will allow you to create truly powerful and insightful data stories.

We will learn about calculated fields, which allow you to create new data values based on the existing data and support effective analytics and data representation. We will look into parameters that let you dynamically change the output of calculated fields or data source connection settings based on the user input. We will also learn about data blending, which helps create charts and controls based on multiple data sources within a report by combining those data sources through blending. Data blending has many interesting applications. A gallery of community visualizations...

Technical requirements

To follow the example implementations in this chapter, you need to have a Google account that allows you to create reports with Looker Studio. Use one of the recommended browsers – Chrome, Safari, or Firefox. Make sure Looker Studio is supported in your country (https://support.google.com/looker-studio/answer/7657679?hl=en#zippy=%2Clist-of-unsupported-countries).

This chapter uses BigQuery, Google Cloud’s serverless data warehouse platform, as a data source in a couple of examples. If you do not already have a Google Cloud account with access to BigQuery, you can create a trial account (https://cloud.google.com/free), which provides $300 of credit for you to use on any Google Cloud resources. You need a valid credit card to enroll in the trial, but you will not be charged. Create a Google Cloud project to start using any resources.

BigQuery charges for the amount of data processed by the queries as well as for the storage of data. It has...

Leveraging calculated fields

Calculated fields are custom fields that you can add to data sources and charts. These fields are derived from existing fields in the data source, including other calculated fields. A calculated field can be either a dimension or a metric.

Looker Studio provides several functions grouped under six categories to help create useful calculated fields. These include the following:

• Arithmetic
• Conditional
• Date
• Geo
• Text
• Aggregation
• Miscellaneous

Calculated fields serve many purposes. They enable you to implement business logic, create user-friendly representations of data, and create complex metrics beyond simple aggregations.

Arithmetic functions enable you to perform mathematical operations such as computing logarithms, exponentials, trigonometric values, or nearest integers on numeric data. You can also do simple math using regular operators for addition, subtraction, division, and multiplication. With date functions...

Using parameters

Parameters in Looker Studio allow both report editors and viewers to input data values to use with calculated fields and connectors. Parameters enable you to create more dynamic reports. There are three ways in which you can use parameters in Looker Studio:

• In a calculated field, to show the results based on the parameter value set by the report editor or chosen by the report viewer
• To pass query parameters to a custom SQL query for the BigQuery connector
• To pass values to community connector parameters

The parameter values can be set and modified in multiple ways:

• The default value in the parameter configuration (by the data source editor).
• Report components – at the chart level, page level, and report level (by the report editor).
• Interactive controls in the report (by report users).
• In the report link by passing the parameter names and values as URL-encoded JSON strings. This allows advanced users to configure reports...

Blending data

Data blending is the process of combining data from multiple data sources. The resultant resource is called a blend. Blends are useful in two primary ways:

• To bring additional information into your visualizations and controls from disparate data sources
• To perform reaggregations, that is, aggregating an already aggregated metric such as calculating the average of averages or the maximum of distinct counts

Often, you may want to analyze data that resides in multiple underlying datasets together. While you can easily visualize this data in separate charts powered by the respective data sources in the report, the challenge is when you want to represent information from these different data sources together in a single component. Blends come to the rescue in such scenarios. Blends incorporate fields from constituent data sources, called tables, and can serve as a source for charts and controls. Through blending, Looker Studio makes it easy for you to combine...

Adding community visualizations

Community visualizations are custom visualizations developed by third-party developers and partners. They are available from the Looker Studio Report Gallery, as well as in the report designer. To display data using community visualizations in a report, they need to be allowed access to the associated data source(s). This option is enabled by default for any data source that uses Owner’s credentials. It can be turned off from the data source editor page. Community visualizations cannot be used with data sources that use Viewer’s credentials.

From the toolbar, select the Community visualizations and components icon. You can choose from the featured visualizations or click on + Explore more to select from the full collection in the gallery:

Figure 7.35 – Adding community visualizations to the report

You are then prompted to grant consent for the report to display the data in the visualization. When consent...

Creating report templates

Report templates allow you to share your reports widely, outside your organization, and with the public. Templates allow others to use your reports with their own data. In Chapter 4, Google Looker Studio Overview, you learned about what report templates are, where to find them, and how to create reports from a template. In this section, you will learn how to create and share a report template.

Template creation is a very simple process and any report can be turned into a template just by adding /preview to the end of its URL. However, there are a few things that need to be kept in mind and followed through to ensure its wider utility.

First and foremost, templates should be based on standard schema data sources or connectors. This makes sure that others will be able to use their own data with the template and create reports from it as needed. Templates made out of non-standard and custom data sources have limited use, if any. You can either share your...

Optimizing reports for performance

Fast report load times and responsiveness are paramount for a good user experience in any visualization tool. Certain design and implementation choices may adversely impact report efficiency. In this section, you will learn about several techniques that will help you optimize Looker Studio reports performance-wise. Some of the considerations here may only be relevant when dealing with truly large volumes of data.

Optimizing data sources

A major reason for lag in Looker Studio is the volume or size of the data being queried. Hence, the first place you can look to for improving the performance of your reports is the data sources.

Modeling the data source

Data sources in Looker Studio are logical constructs and do not pull data from underlying datasets unless this is requested from reports and explorations. Typically, date ranges and other filters defined at the report level determine the maximum volume of data the report can retrieve and...

Summary

In this chapter, you gained an understanding of several advanced concepts in Looker Studio. We explored the corresponding features and looked into some interesting ways to use them. Calculated fields enable you to enrich the data source and manipulate the data to meet your reporting and analytical needs. Parameters allow you to capture user input and use it to perform dynamic calculations, limit the data retrieved from the dataset, and even drive the content displayed in a visual.

Data blending helps you visualize data from multiple data sources together or perform reaggregations. You learned about how to use community chart types and create report templates easily. A report that loads quickly and responsively is important for a good user experience. In this chapter, you also learned about several factors that affect report performance and optimization strategies to address them. This concludes Part 2 of the book, which described the many useful features and capabilities...