Google Data Studio is simply, a tool to tell a story with your data using its charts and tables. It allows you to turn boring reports into more interactive and compact ones.
This article talks about how to use different features of Google Data Studio in detail. It also explains Google Data Studio and its features, advantages, and disadvantages.
Table Of Contents
- What is Google Data Studio?
- How to use Google Data Studio?
- What are the use cases of Google Data Studio?
- How to Connect Data Sources to Google Data Studio?
- What are the Advantages of Google Data Studio?
- What are the Disadvantages of Google Data Studio?
What is Google Data Studio?
It’s a free online tool that allows you to easily visualize data. You have a variety of data sources to choose from, including Google Sheets and Microsoft Excel files. Google Data Studio’s artificial intelligence (AI) automatically combines data from multiple sources, analyses it, and allows you to create interactive charts, dashboards, and reports.
All you have to do now is choose which charts or tables you want to include in your report and apply some colorful themes to them. To become familiar with the tool, you don’t need to go through extensive training sessions. You can create regular project reports, team performance reports, project budget forecasts, and more by simply dragging and dropping charts into the canvas.
Key Features of Google Data Studio
- A Nifty Dashboard: The dashboard and user interface of Data Studio are similar to those of Google Drive. As a result, you’re well-versed in the tool’s user interface. The following are the most important elements with which you’ll interact frequently:
- You can use the top-right Search Data Studio box to look for reports, templates, and data sources.
- You can change the visibility of Reports, Data Sources, and Explorer in the Recent section.
- You can create a new Report, Data source, or Explorer from the left-hand menu. In this area, you’ll also find shared items and the Templates gallery.
- You can customize several fields of the User settings by clicking the gear icon in the top right corner.
- Multiple Data Collection Sources: Data Studio eliminates the need to manage multiple versions of Google Sheets or Microsoft Excel files related to your work. Using 490+ data connectors, the tool can analyze raw data from over 800 data sets. As a result, data from third-party sources such as Funnel, TapClicks, Amazon Seller Central, Asana, Jira Cloud, and others can now be imported. You can also give the tool permission to access and analyze data from Google tools such as Campaign Manager 360, Google Analytics, MySQL, and Google Sheets. When you use Data Studio, you don’t have to be concerned about data integrity or security. It uses advanced encryption technology to protect your data both in transit and within the tool.
- Performance Driven In-Memory BI Engine: Assume you’re presenting a client with a project performance report. Even though you have premium and modern data visualization tools, the presentation isn’t going well because the data keeps loading. Furthermore, when working with multiple data sources, the lag may be even worse. Thanks to the Google Cloud BigQuery team’s BI Engine, Data Studio has sub-second performance. It’s in-memory data access and analysis service that can work with your BigQuery data warehouse on-premise. As a result, you can display real-time data from hundreds of sources in a single dashboard that updates and loads in real-time.
- Interactive Data Visualization: Advanced programming features like chart interaction controls, drill-downs, and cross-chart interactions make the Data Studio report’s view mode extremely responsive. As a result, a viewer can customize almost anything in your reports, from filters to metrics, to gain new insights. Data Studio Explorer allows the viewer to delve deeper into your report by breaking down your graphs and tables into small chunks of information. When viewing the databases of a report, viewers do not need to be SQL database experts. Visual queries are available for viewers to use to explore databases.
- Real-Time Collaboration: You and your collaborators can work on the same Data Studio report in real-time, just like with other Google productivity tools. You can invite people to work with you, manage their access levels, and get a public link for social media from the Share menu at the top of the report. If you share your Data Studio workspace with another person, their Google profile will appear in the menu bar if they join. Other notable features on Data Studio that make collaborative work easier are:
- Allow collaborators to make changes to a reusable data source and incorporate it into their own reports.
- Embed a Data Studio report in a variety of formats, such as newsletters, emails, and blogs.
- Make it impossible for others to print, download, or copy your Data Studio reports.
- Ease of Use: Its web UI is simple to navigate, and Google Workspace users are already familiar with it. Complete drag-and-drop actions are available in the report editing workspace. For each object you use in your reports, you can access custom property panels. You don’t need to know much about graphs and tables if you use Data Studio’s ready-to-use templates. There are eight different types of report categories to choose from in the Templates library.
- Scheduling a Report: It’s crucial to share the data visualization report on a regular basis or according to the client’s preferences. When you’re juggling multiple tasks and looking after your team, it’s easy to forget to send your client project reports. You can plan ahead with Data Studio’s Schedule email delivery feature. You can prepare a report for your client and set a delivery date for it. When the report is due, Data Studio will automatically notify your client. You can also change the Repeat settings to tell the tool if the client requires reports at specific intervals.
- Various Charts and Graphs: You can use Data Studio to create 14 different types of charts for your reports. Whether you need Bar, Pie, or Line charts, you can get the majority of them with just one click. The in-memory BI Engine analyses the data type and organizes it according to the charts or tables you choose. You can add Community visualizations to your report in addition to charts to give it a professional and creative look. You have unrestricted access to various visualizations such as Gantt charts, Radar charts, gauges, Start Ratings, and so on.
How to Use Google Data Studio?
Google Data Studio is simply, a tool to tell a story with your data using its charts and tables. It allows you to turn boring reports into more interactive and compact ones.
- Log in to Data Studio: You’ll need a Google account to access Data Studio, and I recommend using the same one you use for Analytics, Search Console, and/or Google Ads. You’ll be taken to the overview page for Data Studio. To see your dashboard, go to the “Home” tab.
- Familiarize yourself with the dashboard: This dashboard should look very familiar if you’ve used Google Docs, Sheets, or Drive before.
- Connect your first data source: All of the connections you’ve made between Data Studio and your original data sources are listed under data sources. Currently, Data Studio supports over 500 data sources.
- Reports: This is where you’ll find all of your reports (equivalent to a workbook in Tableau or Excel). You’ll notice that you have the option of filtering by who owns the report.
- Explorer: Explorer is a test tool that allows you to experiment with or tweak a chart without having to change the report itself. Let’s say you’ve created a table in Data Studio that displays the most effective landing pages based on conversion rate. “Hmm, I’m curious what I’d find if I added average page load time,” you think as you look at this table.
- Connect to your Data: You can access your data from over 230 connectors through Google Data Studio. These include Google products such as Google Ads, Google Analytics, Campaign Manager, Google Sheets, database platforms like Google BigQuery, MySQL, PostgreSQL, and Google Cloud Spanner, and social media websites like Twitter and Facebook. You can also upload files and extract data.
- Visualize your Data: This is really the fun part. While raw data can mean nothing to the observer, a lot of hidden patterns can be uncovered… like from a secret gold mine, upon visualization. How persuasively you visualize your data can change the minds and decisions of the viewers. The purpose of visualization is to tell a story and Google Data Studio reports help you make your stories more fun.
- Share your Data: You can add people or groups of people to view or edit your reports and data sources. You get to control what rights the viewers have. You can generate URLs to your reports, embed reports in your social media platforms or Google sites, and download your reports as PDF files.
Hevo, a Simpler Alternative to Integrate your Data for Analysis
Hevo offers a faster way to move data from databases or SaaS applications into your data warehouse to be visualized in a BI tool like Google Data Studio. Hevo is fully automated and hence does not require you to code. In fact, even the maintenance required is minimal.
Check out some of the cool features of Hevo:
- Fully Automated: The Hevo platform can be set up in just a few minutes and requires minimal maintenance.
- Real-time Data Transfer: Hevo provides real-time data migration, so you can have analysis-ready data always.
- 100% Complete & Accurate Data Transfer: Hevo’s robust infrastructure ensures reliable data transfer with zero data loss.
- Scalable Infrastructure: Hevo has in-built integrations for 100 plus sources that can help you scale your data infrastructure as required.
- Live Support: The Hevo team is available round the clock to extend exceptional support to you through chat, email, and support call.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects schema of incoming data and maps it to the destination schema.
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
You can try Hevo for free by signing up for a 14-day free trial here.
What are the use cases of Google Data Studio?
- How to Use Templates in Google Data Studio?
- How to Publish your report in Google Data Studio?
- How to Connect to 150+ sources in Google Data Studio?
- How to Create your own report theme in Google Data Studio?
- How to Embed external content in Google Data Studio?
- How to Send scheduled reports in Google Data Studio?
- How to Download reports in Google Data Studio?
- How to Embed reports in Google Data Studio?
- How to Add a date range in Google Data Studio?
- How to Add filter controls in Google Data Studio?
- How to Create interactive chart filters in Google Data Studio?
- How to Add data control in Google Data Studio?
- How to Add a dimension breakdown in Google Data Studio?
- How to Use Data Studio Explorer (Labs) in Google Data Studio?
- How to Create report-level filters in Google Data Studio?
- How to Create blended fields in Google Data Studio?
- How to Blend your data source with itself in Google Data Studio?
- How to Create a basic calculated field in Google Data Studio?
- How to Create an advanced calculated field in Google Data Studio?
- How to Create a calculated blended field in Google Data Studio?
How to Use Templates in Google Data Studio?
There’s no need to start from scratch. If you’re unsure where, to begin with, Data Studio, I suggest looking through their templates for ideas.
Pay attention to the author of the report. The Data Studio team created a number of templates, which you can find in the “Marketing Templates” section. In the “Community” section, however, there are 45+ user submissions. Here are a few of my favorites:
- GA Behavior Overview: This dashboard summarises the most important data from Google Analytics’ Behavior section.
- Paid Channels Mix Report: Use this template to see how your ads are performing across platforms like Facebook, Twitter, LinkedIn, and search.
- Website Technical Performance Indicators: Use this template to see how your ads are performing across platforms like Facebook, Twitter, LinkedIn, and search.
How to Publish your report in Google Data Studio?
- Don’t divulge confidential information. I recommend making a report with publicly available data so you don’t get in trouble for sharing information you don’t own. (Tip: use dummy data from one of Google’s sample data sets to recreate one of your existing company reports!)
- Make it fantastic. Because the public reports are so impressive, don’t be afraid to experiment with design, features, and other elements.
- Toss in some context. With captions, instructions, and possibly a video of you walking through the report, provide on-page explanations of what you’re measuring or monitoring.
How to Connect to 150+ sources in Google Data Studio?
As you can see, data from Google-owned sources such as Search Console, Google Ads, YouTube, and Campaign Manager can be imported into Data Studio.
That, however, is only the tip of the iceberg. There are also over 120 partner connectors, which act as third-party bridges between Data Studio and platforms such as Adobe Analytics, AdRoll, Asana, Amazon Ads, and AdStage (to name a few).
How to Create your own report theme in Google Data Studio?
Whether your report is intended for internal stakeholders such as the leadership team or external stakeholders such as clients, it will be more effective if it is visually appealing.
Click the Layout and theme option in the toolbar to change the report’s style and formatting.
Any changes you make here will be applied to the entire report, so you’ll only have to do it once rather than every time you add a new module.
Simple and simple dark are two of Data Studio’s built-in themes. However, making your own is simple, and the results are far superior.
Select “Customize” from the drop-down menu.
Choose primary and secondary colors, fonts, and text colors based on your brand style guide. You might have to get creative here; HubSpot uses Avenir Next, which Data Studio doesn’t have, so I used Raleway, which is a cousin of Avenir Next.
How to Embed external content in Google Data Studio?
You can bring the rest of the world to your report, just as you can bring the rest of the world to your report.
With the URL embed feature, you can insert Google Docs, Google Sheets, YouTube videos, and even live webpages. Embedded content is far more powerful than a screenshot because it is interactive.
To add content, go to the navigation bar and click “URL embed.”
Simply paste the URL from there. You may then need to resize the box that appears to fit the entire length and width of your content.
There are a lot of options here. One of my favorite ways to use this feature is to embed a Google Form that asks my audience how useful the report was:
If a section of the report requires additional context (or if my audience isn’t particularly technical), I’ll include a short video that explains what they’re looking at and how to interpret the results.
I’ll add the URL of a client’s website, blog, and/or whatever pages they hired me to create or improve to personalize a report for them.
How to Send scheduled reports in Google Data Studio?
Consider using Data Studio’s “scheduled report” feature if you have a group of stakeholders who need to see your report on a regular basis.
Select “Schedule email delivery” from the drop-down menu next to the “Share” button.
Enter the email addresses of your recipients first, then select a schedule, such as daily, every Monday, or once a month.
When working with customers, this is especially useful because you may not want to give them access to the live report.
How to Download reports in Google Data Studio?
You can also save your report to your computer as a PDF. This is useful for one-time situations, such as when your boss requests a status report or a client wants to know how an ad has performed this month.
To download the file, go to the drop-down menu and select “download.”
You can download your current page or the entire report from Data Studio. You can also include a link back to the report so that your audience can learn more about it, as well as password protection to keep your data safe.
How to Embed reports in Google Data Studio?
You can also post your report on your company’s website or in your personal portfolio, which is a great way to show off the results you’ve achieved for a client or project.
On the upper navigation bar, click the brackets icon.
This dialogue box will appear:
How to Add a date range in Google Data Studio?
Allow your viewers to choose which dates they’d like to see information for, giving them more control.
My reports, for example, always default to the previous 30 days, but if one of HubSpot’s blog editors wants to see how their property performed in the previous calendar month, the date range controls allow them to do so.
They can select from predefined options such as “yesterday,” “last seven days,” “year to date,” and so on, or they can specify a custom period.
To enable this, go to the page where you want users to be able to control the date. Next, select “Add a control” from the drop-down menu. Then, from the toolbar, select “Date range.”
On your report, a box will appear. Drag it to the desired location — I recommend the upper right or left corner to ensure that your audience sees it first — and adjust the size as needed.
When you select this module, a panel called Date Range Properties will appear to the left of your report. If it isn’t already, change the default date range to “Auto date range.”
When your visitors use the date range widget to select a date range, all of the reports on the page will automatically update to that time period.
There are two options for getting around this:
Within a specific chart, specify a time period. The date range control will always take precedence over that time period.
With the module, you can group the charts that will be affected by the date range control. Choose Arrange > Group after selecting the chart(s) and the box.
When the date range is changed, only the chart(s) in this group will update.
Make sure your viewers understand this setting; otherwise, they’ll assume that all of the charts on their current page are using the same time period.
How to Add filter controls in Google Data Studio?
With filter controls, you can give your audience even more options. A filter, like a date range control, applies its settings to all of the reports on the page. If, for example, everything except organic traffic was filtered out, all of the reports on that page would only show data for organic traffic.
By clicking this icon in the toolbar, you can add a filter control.
On the report page, the filter will appear. It can be resized and dragged into the desired position. You should see a panel on the left-hand side while it’s selected:
Select which dimension you want viewers to filter in the data tab. These dimensions are derived from your data source — in this case, Traffic Type.
The metric part is not required. Viewers will see the values for each dimension sub-category in the filter if it is checked. (Once you see the screenshot below, this will make more sense.) They can sort by these numbers, but not by metrics.
To your filter control, you can add another filter. If you’ve added a Source / Medium filter, for example, you might want to exclude the “Baidu /organic” filter so that your viewers don’t see it as an option.
In the style tab, you can change the formatting and appearance of your filter control. There are a few options available to you: List/check all the filters that apply, such as this one:
Alternatively, you can use “search all” filters to allow your viewers to search for numeric and text terms using operators like >= and, or “equals,” “contains,” and so on.
This can be inconvenient for those reading the report—plus, they must be familiar with search operators. Stick with the list filter unless your filter dimensions have 10,000 values (which is unlikely).
How to Create interactive chart filters in Google Data Studio?
This may sound complicated, but selecting a dimension in a chart will filter all charts on that page for that dimension.
If you click “organic” in this chart, for example, the other charts on the page will update to show data for organic traffic only, just as if you used a traditional filter control.
For time, line, and area charts, you can also create chart controls. If a user highlights, say, January through March on a time chart, all of the other charts on the page will display data for January through March as well — similar to date range control.
You can also group chart controls, just like filter controls.
Select the appropriate chart to enable chart control. Scroll to the bottom of the right-hand panel and check the box labeled “Apply filter.”
To let your viewers know that interactive filtering is an option, add a caption next to charts that support it:
How to Add data control in Google Data Studio?
Data controls are without a doubt one of the coolest Data Studio features. If you stick one of these bad boys on your report, viewers will be able to choose the source of the data that’s being piped into your charts.
For anyone in charge of a large property or working with multiple stakeholders, this is a game-changer.
Assume you’re the administrator of HubSpot’s Google Analytics account. You create a Data Studio report that tracks key website performance indicators such as average page speed, non-200 response codes, and redirect chains, among other things.
You can also send the report to the Academy team, which has access to academy.hubspot.com’s GA view, and the Leads Optimization team, which has access to offers.hubspot.com.
These teams simply need to select their view from the “data source” drop-down to see this report populated with the relevant data, and voila — all the charts will automatically update.
Not only will you save time by not having to recreate the same report for different groups, but you will also avoid accidentally sharing sensitive or confidential information. Only the data sources to which they have been granted access are available to each viewer.
Multiple data controls can be included in a single report.
By clicking this icon, you can add the data control widget to your report:
How to Add a dimension breakdown in Google Data Studio?
It’s easier to show you how a dimension breakdown works rather than telling you what it is.
Let’s say we want to see users based on their source. We make a simple bar chart to find out.
This is intriguing, but there is a lack of context. Is all of that organic traffic, for example, coming from Google? (This is probably because the data is from the United States, but imagine making the same chart for China or Japan, where Baidu and Yahoo have a much larger presence.)
What about traffic from referrals? Clearly, referral links are bringing in a sizable number of users; is the majority of this traffic coming from a single source, or is it evenly distributed across a variety of sources?
We could make separate bar charts for each source by filtering by medium first, then adding “Source” as a dimension and “Users” as a metric.
We could also use Data Studio to automate the process with a single click.
Click “Add dimension” under Breakdown Dimension.
“Source” should be added.
Here’s what you’ll want to look at:
To make your regular bar chart into a stacked bar chart, go to the “Style” tab and check the box “Stacked bars” (you should see the chart type update accordingly).
Data Studio will make your bar charts “100% stacking,” which means that every bar will appear at the top of the chart. However, this style is deceptive; for example, it implies that each medium attracted the same number of users.
Remove the checkmark from this box.
How to Use Data Studio Explorer (Labs) in Google Data Studio?
To open Explorer, hover your mouse over the space next to the chart’s top-right corner. Three vertically stacked dots will appear; click on them.
“Explore (Labs)” should be selected.
You’ll notice something similar to this:
You can switch between visualisations, add and remove dimensions and metrics, adjust the date range, and apply segments.
Note that, unlike every other Google tool, Explorer does not save your work automatically.
Click the “Save” button on the top nav bar to save your chart (to the left of your profile icon). Your Explorer “report” will be saved in the Explorer section of your dashboard once you’ve done that. Furthermore, by default, every change you make will be saved.
If you want to start with Explorer instead of the dashboard, that’s fine (rather than a Data Studio report). Select “Explorer (Labs)” from the left-hand menu on your Data Studio dashboard.
By clicking the blue button in the lower right corner, you can add a new data source.
Explorer perplexed me at first. What was the point of having both? It feels very similar to the core Data Studio.
However, after spending some time in Explorer, I’ve realised how valuable it is.
In contrast to Data Studio, any changes you make to a chart in Explorer are only temporary. That means it’s a great place to dig into your data and experiment with different visualisations without committing to anything permanent. After that, simply export your chart back into Data
Then decide whether you’d like to incorporate your Explorer findings into a new or existing Data Studio report.
How to Create report-level filters in Google Data Studio?
A filter is applied to every chart on that page by default. What happens, however, if the viewer moves on to the next page? They aren’t compatible with the filter.
For non-technical people, this is perplexing, and for data-savvy people, it is inconvenient. Simply right-click on a filter and select “Make report-level” to raise it from page-level to report-level.
How to Create blended fields in Google Data Studio?
One of the most prominent features you can find on the sidebar is Blend Data. You can add data using this option to blend it with your current data. As long as there is a Join key, you can blend two data sources and get a more complete picture. Here is an example.
First, you can add your data using the ‘Add Data’ option.
After adding the data to Google Data Studio, you can blend two data sources.
Both of the data sources have a common field – ‘Year’. In one of the data sources, there is a random metric called ‘number’, that I have added, and in the other, there is the population of the world for that year.
And here is the blended table after you save the changes.
The rest of the features change with the type of chart you use and are pretty intuitive to figure out.
How to Blend your data source with itself in Google Data Studio?
Data Studio is useful because it allows you to combine data from over 400 different sources into a single report. But now, thanks to a new feature called blended sources, it’s even more powerful.
Warning: this is going to get a little technical. I promise it will be worthwhile if you stick with me.
If you’re familiar with SQL’s JOIN clauses, you’ll have no trouble understanding data blending. Do you have no idea what SQL is? It’s not an issue.
A Venn Diagram is the best way to think about blending data. You have two sets of data. Each data set has its own set of characteristics, such as the data in the green and blue
They do, however, share (at least) one data point: the data in the blue-green overlap section.
A key is a term that refers to a shared data point. Your data sets won’t blend if they don’t have a key.
Consider the following scenario: you want to compare how users interact with your website versus your app. The key is the user ID, which is a Google Analytics custom dimension that your app analytics software also uses. (It’s worth noting that the key doesn’t have to be named the same in both data sources; it just needs to have the same values.)
You combine your Google Analytics website behavior report with your app usage report. This returns all of the records from the first report, as well as any matching records from the second; in other words, if a user has visited the site and used the app, they will be included.
They will not be included in the new blended data if they only used the app and did not visit the website.
A LEFT OUTER JOIN is what this is called. Because the order in which your data sources are arranged is important.
Put your primary data source first — for example, the one where you want all the values regardless of whether your second source matches.
To begin, include a chart in your report.
Select “Blend Data” from the drop-down menu.
The following panel will appear:
On the left, choose your first data source. Keep in mind that this is the main data source. Then you’ll want to add your second data source. In Data Studio, you can add up to five data sources to a chart, but for now, we’ll stick to two.
Select your join key now (s). The field will turn green if it exists in both sources. You’ll see this if it doesn’t exist:
The key serves as a filter for the second data source, so keep that in mind. Only records matching the landing page from the GA view for hubspot.com will be pulled from Google Search Console in this example.
The number of records pulled from the second data source will be reduced even more if you use multiple keys.
The rest of the process should be familiar once you’ve chosen your join key(s).
For your first data source, choose the dimensions and metrics you want to see. Then repeat with your second.
You can also use a filter or a date range to narrow down the results (or for GA sources, segments). Filters, date ranges, and segments applied to the left-most data source will be carried over to the others.
Click “Save” once you’ve finished customizing the report.
Data Studio provides a great shortcut if you prefer to create two separate charts and then combine them.
Simply right-click both charts and select “Blend data.”
How to Blend your data source with itself in Google Data Studio?
If you’re having trouble with your data source connectors, try this workaround: a data source that is blended with itself
For example, the GA data connector only allows you to add one “active user” metric to a chart, so you can’t see 1 Day Active Users, 7 Day Active Users, and 28 Day Active Users on the same chart… Unless your Google Analytics data source is blended with itself.
Follow the same steps as before, but instead of selecting a new data source for your second, choose the first one again.
Because all of the fields are identical, you can use any join key you want.
When comparing trends across two or more subdomains or segments, this option is ideal.
I wanted to look at organic users for both the HubSpot Blog (blog.hubspot.com) and the main site (www.hubspot.com) at the same time, for example.
This allows me to see if our search traffic is increasing across the board. When traffic drops, it’s also useful to see if rankings have dropped site-wide or just for the blog (or the site).
You can’t, however, add two different “user” metrics to a chart at the same time… Unless you’re blending data, of course.
To do so, create a new blended data source (following the same steps as before).
Fill in the first column with your first view, the second column with your second view, and so on.
The join key is “Date.”
You included the organic traffic segment in both sources, but you can pick and choose which one you want (paid traffic, social traffic, etc.) Alternatively, turn it off completely! There are a lot of options here.
Here are some more suggestions for blending a source with itself:
- Compare and contrast two or more custom segments.
- Compare and contrast two or more landing pages.
- Compare the results of two or more goal completions.
How to Create a basic calculated field in Google Data Studio?
It’s time to create a calculated field if your existing data isn’t providing you with enough information.
Calculated fields take your data and perform calculations, as the name implies.
The best way to explain it is to use an example.
Let’s say you want to know how many transactions each user has on average. You can make a calculated field that divides the “Transactions” metric by the “Users” metric.
This field will be automatically updated once it’s been created, so you can change the chart’s time range, dimensions, and so on, and the average transactions per user data will update as well.
A calculated field can be created in two ways.
How to Create an advanced calculated field in Google Data Studio?
Let’s say you majored in English and you’ve always been annoyed by the lower-case “Source” in Google Analytics.
To convert Source to all upper-case letters, use the UPPER function.
“Add dimension” > “Create new field” is all it takes.
After that, use the UPPER formula:
This trick will also standardize any custom naming, as Google Sheets expert Ben Collins points out; for example, if some people on your team used “chat” for a campaign and others used “Chat,” the UPPER function will aggregate both.
Perhaps you’d like to make a new city and country field.
Simply select “Add dimension” > “Create field” (since city and state are categorical rather than quantitative variables).
Then, using the CONCATENATE function, smush the City and Country fields together.
CASE is one of the coolest. It’s essentially an IF/THEN statement if you’re not familiar with it. You can use this function to make your own groupings.
Let’s pretend you’re looking at the table we made in the previous step:
Facebook mobile traffic (m.facebook.com) and desktop traffic (Facebook) are treated as two separate sources in Data Studio. There’s also l.facebook.com, which is desktop traffic that comes through a link shim that Facebook put in place in 2008 to protect users from spam. What if you wanted to pool all of your Facebook traffic into one place?
This problem is easily solved using the CASE formula. The formula is as follows:
CASE WHEN condition THEN result WHEN condition THEN result ELSE result END
You can have one condition (as in the example below) or multiple conditions. The ELSE argument is optional, so if you don’t need it, leave it out.
The formula we’ll use to group Facebook traffic is as follows:
CASE WHEN REGEXP_MATCH(Source,"^(l.facebook.com|m.facebook.com|facebook.com)$") THEN "Facebook" END
“If the source matches l.facebook.com, m.facebook.com, or facebook.com, call it Facebook,” this formula tells Data Studio.
You must be able to edit the data source in order to add a CASE formula.
To open the data field editor, click the pencil icon next to your source.
Then, in the upper right corner, click “Add a new field.”
Put your formula in the box.
A green checkmark will appear if the formula is correct. Click “Save” after giving your new field a name. This field can now be added to any chart or data visualization that uses this data source.
How to Create a calculated blended field in Google Data Studio?
This is the pinnacle of Data Studio mastery, requiring all of your previously acquired skills as well as a healthy dose of luck — just kidding, it’s ridiculously simple.
As usual, create a blended data source.
I combined the GA views for www.hubspot.com and blog.hubspot.com in this example.
Then, as you would for a normal calculated field, click “Add metric” > “Add new field.”
Put your formula in the box.
I wanted to see “Total Users” (i.e., users from both www.hubspot.com and blog.hubspot.com), which is a straightforward calculation:
If you’re using two fields with the same name, as I am, things can get a little complicated. Data Studio is sometimes capable of distinguishing between the two, and other times it isn’t.
If you have problems, try changing the name of one or both fields in the original data source(s), which you can do at any time by clicking the pencil next to the blended data source.
Then, next to the field you’d like to change, click the pencil.
This pane will appear; change the title as needed.
Then, to update the formula, click “Save” and return to your calculated field:
How to Connect Data Sources to Google Data Studio?
Here’s how to connect data sources to Google Data Studio step by step.
- Start with Analytics or Search Console.
I’ll connect Analytics in this example, but the process is nearly identical for other sources.
Connect the Google Analytics Demo Account for the Google Merchandise Store if you want to do exactly what I’m doing.
You will be asked to approve the connection. After that, you’ll need to choose an account, a property, and a view.
You’ll see something similar to the image below: a list of all the fields in your Analytics account (both standard and custom fields).
Add new fields, duplicate existing ones, turn them off, change field values, and so on in this step. Of course, we could do all of that in the report itself, which is much more convenient.
- Click “Create Report” in the upper right: You’ll be asked if you want to add a new data source to the report, and the answer is yes.
- Click “Add a chart” in the toolbar: It’s now time to create your first chart. The good news is that data Studio makes comparing chart types simple thanks to some helpful illustrations.
- Choose the first option under “Time series.”: You’ll begin with a “Time series” chart for the purposes of this tutorial. This type of graph depicts change over time. The right-hand pane will change once it appears on your report. Here’s what you’ll want to look at:
The dimension is set to “Date” by default, but you can change it to any of the time-based dimensions, such as “Year,” “Hour,” and so on.
Because the Demo Account doesn’t have a lot of historical data, I’ll stick with “Date.”
Data Studio will choose a metric (what appears on the Y-axis) for you automatically. Feel free to change this; for example, for me, it defaulted to “Pageviews,” but I’d prefer to see “Revenue per user.”
- Add another metric.: To begin, make sure you’ve selected the chart so you can see the right-hand pane:
When it comes to adding a metric, you have two options (or dimension).
You can either drag a field from the right into the metric section or click the blue plus-sign icon to bring up a search box where you can find the field you want.
Simply hover your mouse over a metric and click the white “x” that appears to delete it.
- To add a table, choose the third option under “Add a chart.”:
My chart’s default dimensions and metrics are Medium and Pageviews, so I change them to Product and Unique Purchases.
And I believe the formatting of this table could be improved.
Change the “Rows per page” to 20 (much easier to read) and check the box to include a Summary row.
- Finally, click “Style” to go to the Style tab: Select “Add border shadow” from the drop-down menu. This is one of my favorite techniques for making a data visualization stand out.
- To see the finished product, click “View” in the top corner.: This changes your mode from Editor to Viewer.
- Click “Edit” to finish up and name the report.: To change the title, double-click it (it’s currently “Untitled Report”).
The first report is now officially completed. To share your report, click the familiar icon above the Chart Editor and enter some email addresses.
What are the Advantages of Google Data Studio?
1. Cloud-based and Completely Managed
Unlike most popular business intelligence tools like Power BI, Tableau, etc. Data Studio was designed from the ground up as a cloud-based service. It is a completely managed service which means the user does not have to manage any kind of infrastructure or installation.
2. Tight Integration with Google’s Ecosystem
The biggest advantage offered by Data Studio is its ability to integrate seamlessly with Google applications like Google Analytics, Big Query, Google Sheets, etc. So if your ETL architecture is primarily built on top of Google applications, you will save a lot of time when integrating with Data Studio.
3. Easy to Use
Data Studio offers a very easy-to-use UI that will help anyone acquainted with Google products to start creating reports and dashboards within a few clicks. In that sense, it offers a very flat learning curve.
4. Access and Sharing Controls
Being from the Google family, it inherits the granular access control and sharing mechanisms that are typical of the Google office suite. Sharing reports and dashboards to other users and restricting access with a high degree of granularity is very easy in Data Studio.
5. Support for Live Connections
When compared to other BI tools like Power BI, Tableau, etc, Data Studio is designed on the premises of a live data connection. This means there is no elaborate logic or scheduled jobs required to manage the freshness of data. Anytime a report or dashboard is accessed or refreshed in UI, it will fetch the latest data. If the resultant performance hit seems too much for you, it is possible to adjust the fetch using cache settings.
6. Free of Cost
Data Studio is offered free of cost at this point and is bundled with Google cloud services. The storage cost for data and processing costs for transformation is outside of this.
What are the Disadvantages of Google Data Studio?
1. Lack of Real-time Updates in the Dashboard
Even though the live connection is supported for most data sources, there is no built-in method at the moment to keep a dashboard or report view auto refreshed. So if you want to project a real-time updated dashboard to motivate your team, you will have to look beyond built-in Data Studio features. A workaround using a third-party browser extension is possible to accomplish this use case. If you are interested, you can find out more about this here.
2. No Support for Excel
Being a Google product, Data Studio disregards standard business intelligence data formats like Excel and prefers Google-based services instead. Excel can be supported by converting it to a CSV file or a Google Sheet
3. Lack of Comprehensive Function Support
Data Studio is still nowhere close to the number of built-in data processing functions supported by Tableau and Power BI. It even misses some basic functions like SUMX present in Power BI that helps to compute the sum of columns considering both rows and columns.
4. Slow Speed in Case of Live Connection
One consistent feedback about Data Studio is that loading the dashboard becomes exponentially slow with the increase in complexity of functions that are part of the view. This is a side effect of the live connection mechanism and the workaround is to use a scheduled extract in cases where performance is critical.
5. No On-premise Deployment Option
For organizations with strict data security requirements, the lack of an on-premise option is a big setback. Such organizations will prefer business intelligence tools like Tableau, Power BI, etc. The latter tools provide desktop installation support and the ability to access data within their internal network.
6. Lack of Native Connector Support for Cloud-based Data Sources
Data Studio lacks native connector support for some of the most frequently used cloud-based data sources like Hubspot. Even though there are a partner and community-based connectors to cover some of them, these are paid offerings.
7. Complex Visualizations Not Possible
Even though it is easy to set up basic visualizations in Data Studio, it does not support the kind of flexibility and customizability that is offered by tools like Tableau. So organizations with analytical needs and expert analysts may find Data Studio lacking in visualizations.
Google Data Studio allows you to create reports with great visuals. It is very convenient if you use other Google products like Google Analytics. It is easy to share and view. But note that there is no desktop tool and the tool is not as suited to complex data transformations as say, Power BI. But if you want a tool to work with your ready-to-use data and you don’t need to perform too much cleaning, then Google Data Studio is perfect for your reporting needs. What’s more? It is free!
If you are working with multiple sources of data, ranging from databases to SaaS applications, you might find it difficult to integrate all the disparate data. Hevo is a top-notch data integration tool that lets you move data from several such sources to any destination in real-time so that you can perform analytics seamlessly.
If you want to see how it works firsthand, please sign-up for a 14-day free trial. You will absolutely love it.
Tell us what you think about Google Data Studio in the comments. We would love to hear from you!