10 Data Studio Interview Questions and Answers

Data Studio is a powerful tool for creating interactive and shareable dashboards. It allows users to visualize data from various sources, making it an essential asset for data analysis and reporting. With its user-friendly interface and robust features, Data Studio enables professionals to transform raw data into meaningful insights, facilitating better decision-making processes.

This article offers a curated selection of interview questions designed to test your proficiency with Data Studio. By reviewing these questions and their answers, you will be better prepared to demonstrate your expertise and effectively communicate your skills during your interview.

Data Studio Interview Questions and Answers

1. How would you blend data from two different sources? Provide an example scenario.

Data blending in Data Studio allows you to combine data from different sources into a single chart or report. This is useful when you have related data stored in different places and want to analyze them together.

To blend data, you need a common key or dimension in both data sources. Data Studio uses this key to join the data.

Example Scenario: Suppose you have two data sources: one from Google Analytics tracking website traffic and another from a CRM system tracking sales data. You want to create a report showing the relationship between website visits and sales.

Steps to blend data:

• Add both data sources to your Data Studio report.
• Create a new chart or table.
• In the data tab, click on “Blend Data”.
• Select the common key (e.g., Date) from both data sources.
• Choose the metrics you want to display from each data source (e.g., Sessions from Google Analytics and Sales from the CRM system).
• Apply the blend and customize the chart as needed.

2. Write a formula to create a calculated field that shows the percentage change between two metrics.

In Data Studio, a calculated field allows you to create new metrics based on existing data. To show the percentage change between two metrics, use the formula:

((Metric2 - Metric1) / Metric1) * 100

Here, Metric1 represents the old value, and Metric2 represents the new value. This formula calculates the difference between the two metrics, divides it by the old value, and then multiplies by 100 to convert it to a percentage.

3. How do you apply a filter to show only data from the last 30 days?

To show only data from the last 30 days, use a date range filter. This filter updates automatically based on the current date.

Steps:

• Open your report in Data Studio.
• Select the chart or table you want to filter.
• In the properties panel, find the “Data” tab.
• Under “Date Range Dimension,” select the date field you want to filter by.
• Click on the “Date Range” dropdown and select “Advanced.”
• Choose “Last 30 days” from the options.

4. Write a formula to create a calculated field that categorizes sales into “High”, “Medium”, and “Low” based on specific thresholds.

To categorize sales into “High,” “Medium,” and “Low” based on specific thresholds, use a CASE statement within a calculated field:

CASE
  WHEN Sales > 1000 THEN "High"
  WHEN Sales > 500 THEN "Medium"
  ELSE "Low"
END

5. Explain how to integrate BigQuery with Data Studio and provide an example use case.

To integrate BigQuery with Data Studio:

• Open Google Data Studio and create a new report.
• Click on “Add Data” and select “BigQuery” as the data source.
• Authorize Data Studio to access your BigQuery data.
• Select the appropriate project, dataset, and table from BigQuery.
• Add the selected data to your report and start creating visualizations.

Example use case: Suppose you have a large dataset of sales transactions stored in BigQuery. You want to create a dashboard in Data Studio to visualize sales performance metrics such as total sales, average order value, and sales trends over time.

6. Explain how to transform data within Data Studio using functions and calculated fields.

In Data Studio, transforming data is achieved through functions and calculated fields. Calculated fields allow you to create new metrics and dimensions based on existing data.

Functions in Data Studio perform operations on your data. These functions can be mathematical, text-based, date-related, or aggregation functions.

To create a calculated field:
1. Open your Data Studio report and select the data source you want to modify.
2. Click on “Add a Field” to create a new calculated field.
3. Enter a name for your calculated field and define the formula using available functions.

Examples:

• Mathematical Function: SUM(Sales) * 1.1 to increase sales by 10%.
• Text Function: CONCAT(FirstName, " ", LastName) to combine first and last names.
• Date Function: YEAR(Date) to extract the year from a date field.
• Aggregation Function: AVG(Score) to calculate the average score.

7. Describe the steps to create a custom visualization using the Community Visualization feature.

To create a custom visualization using the Community Visualization feature:

1. Set Up Your Development Environment: Ensure you have Node.js and npm installed. Use the Data Studio CLI to create a new visualization project.
2. Create the Manifest File: This file (manifest.json) contains metadata about your visualization, such as its name, description, and the fields it uses.
3. Develop the Visualization: Write the JavaScript, HTML, and CSS code to define how your visualization will look and behave. Use the Data Studio JavaScript API to interact with the data.
4. Deploy the Visualization: Host your visualization files on a web server. You can use platforms like GitHub Pages or Google Cloud Storage.
5. Register the Visualization: In Data Studio, go to the Community Visualizations section and register your visualization by providing the URL to your manifest file.
6. Use the Visualization: Once registered, you can add your custom visualization to any Data Studio report and configure it with your data.

8. Explain how to troubleshoot data discrepancies between Data Studio and the original data source.

To troubleshoot data discrepancies between Data Studio and the original data source:

1. Verify Data Source Connection: Ensure that Data Studio is correctly connected to the original data source. Check for any connection errors or issues that might affect data retrieval.

2. Check Data Freshness: Confirm that the data in Data Studio is up-to-date. Data Studio might cache data, leading to discrepancies if the original data source has been updated recently.

3. Compare Metrics and Dimensions: Ensure that the metrics and dimensions used in Data Studio match those in the original data source. Differences in naming conventions, data types, or calculations can lead to discrepancies.

4. Review Data Transformation: Examine any data transformations or calculated fields applied in Data Studio. Ensure that these transformations are consistent with those in the original data source.

5. Inspect Filters and Segments: Check for any filters or segments applied in Data Studio that might exclude or alter data. Compare these with the filters or segments in the original data source.

6. Audit Data Sampling: Data Studio might use data sampling for large datasets, which can lead to discrepancies. Verify if sampling is applied and compare it with the original data source.

7. Examine User Permissions: Ensure that the user permissions in Data Studio and the original data source are consistent. Discrepancies might arise if users have different access levels or data visibility.

9. Describe how to use filters and segments to focus on specific data subsets.

Filters in Data Studio refine the data displayed in your reports. You can create filters to include or exclude data based on specific conditions. For example, you can filter data to show only users from a particular country or transactions above a certain value. Filters can be applied to individual charts, pages, or the entire report.

Segments allow you to group data into meaningful categories. For instance, you can create a segment to analyze the behavior of new users versus returning users. Segments can be dynamic, meaning they update automatically as new data comes in, or static, where the data is fixed at the time the segment is created.

To create a filter:

• Select the chart or component you want to filter.
• Click on the “Add a filter” option.
• Define the filter conditions, such as including only sessions from a specific country.

To create a segment:

• Go to the “Segments” section.
• Click on “Create Segment.”
• Define the criteria for the segment, such as users who have made a purchase in the last 30 days.

10. Create an advanced calculated field that combines multiple metrics and dimensions.

In Data Studio, calculated fields allow you to create new metrics and dimensions by applying mathematical operations and functions to existing data. This is useful for creating advanced metrics not directly available in your data source.

To create an advanced calculated field that combines multiple metrics and dimensions, use a combination of arithmetic operations, functions, and logical expressions. For example, to calculate the average revenue per transaction:

Average Revenue per Transaction = SUM(Revenue) / COUNT(Transactions)

You can also use conditional expressions for more complex fields. For instance, to categorize users based on purchase behavior:

CASE
  WHEN SUM(Revenue) > 1000 THEN 'High Value'
  WHEN SUM(Revenue) BETWEEN 500 AND 1000 THEN 'Medium Value'
  ELSE 'Low Value'
END