The WHEN condition takes any boolean expression. WHEN condition: It analyzes your data and returns true only if the condition is met- otherwise, it returns false. Let’s look at its syntax and its meaning. In between is where you place clauses or sections. WHEN Country IN ("Spain","Italy") THEN "Europe"Ī CASE statement must begin with the keyword CASE and end with the keyword END. WHEN Country IN ("India","China","Japan") THEN "Asia" For instance, you can group countries into their respective regions. One of the most common uses for the CASE function is to create a group of data or categories. Let’s look at an example for the CASE function. It allows you to set a default result if no conditions are met. The CASE function evaluates a list of conditions, then returns the first result to match the expression. Take advantage of the advanced CASE functionĭata Studio has an advanced CASE function to help you achieve more when organizing and sorting data. Step 5: Click ‘Save’ and view your report. Step 4: Configure join by selecting the join operator and the join conditions. Step 3: Click on join another table, and then select the data source. Step 2: Select any element and click the ‘Blend Data’ option under the ‘DATA’ panel on the right. Step 1: Open a Google Data Studio report. It also contains a condition-set of fields-that determines how the tables relate. A join configuration features an operator which defines how to join both non-matching and matching records from the tables. Before you get started, you need to understand different join configurations since they help link tables. Note that each blend can take a maximum of five tables. These tables have fields that are sourced from the underlying data source. When you create or edit a blend, a list of the tables appears on the UI. They have no credential settings or data freshness since they inherit them from the underlying data source.īlends consist of tables from different sources.Blends get data from multiple data sources.Blends are not re-usable across other reports.But, don’t confuse data blending with data sources as they have several differences. Initially, Data Studio featured the LEFT JOIN only, but now they have added four other joins: INNER JOIN, RIGHT (OUTER) JOIN, CROSS-JOIN, and FULL (OUTER) JOIN.īlending data creates a resource called a blend, which works similarly to data sources. For instance, you can merge data from your Google Ads, and Google Analytics accounts to see how your marketing campaigns perform in a unified view. The blend editor is designed to help marketers and analysts work smarter with the drag and drop features.īlending in Google Data Studio helps users create table controls and charts based on many data sources. Thanks to Data Studio’s blend editor, you can join data from different sources without typing a single line of code. But, if you’re running a smaller company without large hiring budgets for those roles, you might think advanced data analysis isn’t in the cards for you. Create dimensions using calculated fieldsĭata analysts and architects often rely on SQL and languages alike to join data from different tables. ![]() Automate your data transfers with community connectors.This article will walk you through the most advanced tips for marketers and analysts. Simply put, the advanced features Data Studio has to offer can help you, your clients and stakeholders increase accuracy, simplify your workflow, and produce more reliable data visualizations. Unfortunately-but fortunately for those of you reading-most people only know how to use the basic features in Google Data Studio and are not aware of certain advanced capabilities that can take their data game to the next level. As a result, Data Studio has quickly become one of the most used and insightful data visualization tools out there. More importantly, the Data Studio team has always listened to the community and taken its feedback seriously. Since Google Data Studio’s beginnings in 2016, new features and updates have been rolling out frequently to improve the platform and move the needle on data visualization.
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