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You can easiliy create a report following this step :
To start exporting your data to Google Sheets, you need to install the Catchr add-on. You currently have two options :
Option A: Via the marketplace:
Option B: Directly within a Google Sheets:
Once you have installed the add-on, you can start making requests.
Looker Studio (formerly Google Data Studio) is an essential dashboard tool. However, despite its many advantages, one significant issue is its slow performance. Don't worry, though - you're not the only one facing this issue, and we'll explore different solutions to fix it.
Let's get started!
Looker Studio operates by running a query for each new table or graph, waiting to obtain the requested data, and then applying formatting to display the data. These steps are performed for all data sources in real-time, which is the main reason why Looker Studio operates slowly.
This is the process carried out by Looker Studio the first time you request the data, after which it will be cached. As a result, your dashboard will load faster when you open it a second time. However, if you request a different date range or new metrics and dimensions, Looker Studio will need to query the data source again.
ℹ️ Please note that the duration for which the data is cached is determined by settings and depends on the connector used. For more information, please refer to Looker Studio support.
So, your Looker Studio dashboard may run slowly if you:
To speed up Looker Studio, there are multiple solutions more or less efficient:
The more charts and tables you have, the slower Looker Studio will be. It's best to create a concise dashboard with fewer metrics and dimensions. Avoid displaying numerous data on a single page, as Looker Studio will take longer to retrieve and display the data. It's better to have multiple pages with a few charts each rather than one page with many.
Consider using a clear and optimized Looker Studio dashboard template, which is available for free and can help you save time while analyzing your data.
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As previously stated, Looker Studio will request data from the data source for all charts and sources added. If there are too many data sources on the same page, the loading time may be excessively long. To resolve this, we strongly recommend separating different data sources into multiple pages. Create charts that use the same data source on a page. For example, when creating a social media dashboard, you can confidently place your Facebook Ads data source charts on the first page and your Instagram data source charts on the second page.
The more filters and data that are applied, the longer it will take for Looker Studio to load the data. While filters are great for data analysis, it's best to use them sparingly!
Cross-filtering is also a part of this, and you can disable it on certain visuals to reduce the use of filters. To do this, go to chart set-up, scroll down to find the chart interactions parameters, and uncheck cross-filtering.
The Extract data connector enables you to choose particular fields from a data source and keep only the essential information. The selected fields will be updated automatically based on the frequency you set, but it’s not a real-time request. Please note that the storage capacity is limited to 100MB.
This feature is useful for accessing specific data or performing exploratory analysis, although it has restrictions on the selected data.
When you're editing a report, go on resource, then manage added data source and search "Extract data":
Click on the Google connector displays.
Then, choose your data source, choose your fields, check auto-update and choose the update frequency.
After that, you can click on "Save and Extract", and "Add".
Your extracted data source is now available on your report!
Source: Support Looker Studio - Extract Data connector
Finally, you have the option to use Google Sheets or BigQuery as your database. It's important to note that Looker Studio's performance is most affected by making queries to platforms such as Facebook, Google Analytics 4, Twitter, and others. Therefore, we aim to avoid direct requests from Looker Studio to these platforms by using Google Sheets or BigQuery.
Unlike the Extract data connector proposed by Looker Studio, going through an intermediary removes the 100 MB storage limit. Google Sheets has a limit, but it's hard to reach, and Google Big Query doesn't have one.
Connecting Google Sheets or Google Big Query to Looker Studio will greatly reduce loading times, while still allowing you to use your up-to-date data.
Now, we will present you how to connect your data on Google Sheets and Big Query using Catchr’s connectors, then how to connect Google Sheets/Big Query to Looker Studio to create your dashboard!
To accomplish this, Catchr provides a Google Sheets Add-on. With this add-on, you can easily import data from over 50 different sources into Google Sheets. Your data will be automatically and regularly updated based on the frequency you choose.
Here's a video that explains how to use it:
There are two ways to create your dashboard with the data you've imported:
▶️ Directly on Google Sheets
Click on Extensions > Looker Studio > Create a report
This tab will open:
Check the option you want then click on “Create” button.
Your report has been created with your data!
▶️ Directly on Looker Studio
Go to Looker Studio, then Create > Report.
Find “Google Sheets” native connector.
And choose your spreadsheet. Check the option you want and click on “Add” button on the bottom right.
You’re data are available on Looker Studio!
To achieve this, you can utilize Catchr’s connector to integrate your data with BigQuery. There are over 50 different sources available. Your data will be updated automatically and regularly, based on the chosen frequency.
Here's a video that explains how to use it:
As for Google Sheets, you can create your report from Big Query or directly from Looker Studio.
▶️ Directly on Big Query
From a table in Big Query, click on the Export tab > Explore with Looker Studio
Your data will be imported directly into a new report that you can modify.
▶️ Directly on Looker Studio
Go to Looker Studio, then Create > Report.
Find “BigQuery” native connector.
Now you can use your data from Big Query.
To enhance Looker Studio's performance, you can follow these 5 methods: reduce dashboard complexity, separate data sources by page, minimize filters and calculated fields, utilize the extract data connector, and use Google Sheets or Big Query for data collection. These solutions can also be combined to maximize Looker Studio's efficiency.
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