Comparison: Data Studio vs Looker

Last December, Google rebranded “Google Data Studio” to “Looker Studio” after acquiring Looker earlier in February 2021. Looker and Looker Data Studio are both Google tools with a lot in common. They are both strong BI solutions that provide data analytics, integration, and visualization to assist enterprises in overcoming business challenges. 

January 18, 2023 - Last December, Google rebranded “Google Data Studio” to “Looker Studio” after acquiring Looker earlier in February 2021. Looker and Looker Data Studio are both Google tools with a lot in common. They are both strong BI solutions that provide data analytics, integration, and visualization to assist enterprises in overcoming business challenges. 

    Let’s start by taking a look at a side-by side feature comparison:

    Features Data Studio Looker
    Price Free From USD 3K per Month
    Data Source Integration Both SQL and non-SQL SQL
    Data Source Merging Yes Yes
    Fully-Hosted on Cloud Yes Yes
    On-Prem Deployment Yes Yes
    Linux/Windows Deployment No No
    Basic Data Modeling Yes Yes
    Advanced Data Modeling No Yes
    Predictive Analytics No Yes
    Free Version Yes No
    SQL Support Yes Yes
    API Access Yes Yes
    Custom Visualization Yes Yes

    Now that you have an overview, let’s do an in-depth comparison between Google Data Studio vs Looker: 

     

    Getting Started

    Data Studio:

    You don’t need to login to your  Google account to view a report in Google Data Studio. But, if you want to create or edit reports, you should login to your Google account. 

     

     

    Looker:

    You will need to create an account. 

    1. Go to LOOKER.COM. 
    2. Click the Request a Demo button. 
    3. Enter the required details 
    4. Click submit. 

    After the approval of the submitted application, you will be eligible to use the trial version. Also, when you use Looker, you don’t need to complete any installation process, configuration, or maintenance.

    Note: Both of these BI tools are cloud hosted.

     

    Data Integration      

    Data Integration can be divided into two parts: Data Source Types and Merging types

                 Data Sources:

                      Data Studio:

    This tool is a native integration to Google application, so users will be able to use  most of the native Google sources such as Google Analytics, Google Sheets, Google Ads, BigQuery, Cloud Storage etc. In addition, Data Studio can access over 400 other data sources, including Facebook, Adobe Analytics, and JASON. As a result, Google Data Studio is able to collect data from each of the sources listed and is compatible with both SQL and NoSQL data sources

     Looker:

    Looker uses an entirely different approach compared to Google Data Studio. For instance, to integrate data using Looker, you first need to transfer that data to an SQL database. If you don’t, Looker won’t be able to read the particular data set. Currently, Looker is compatible with over 50 databases such as Google BigQuery, Amazon Redshift, and Snowflake.

     

    Merging Data Types:

                       Data Studio:

    Google Data Studio comes with a data blending ability. With this feature, you can easily merge up to 4 different data sources and create charts depending on various data types. Additionally, as this feature is only accessible at the report level, the data source’s home page will not be displayed.

                     Looker:

    Looker uses the Explores feature to merge data. This is a handy feature that can merge any data type. After merging the data, you should be able to display results in a single table. Then examine the pivot table and data. If you want, you can create any visualization.

     

    Data Modeling

    Data Studio:

    You have the option to alter the fields in a given data source when you add it to the data studio. This feature becomes available immediately after you connect the data set to the studio. You can customize these fields by altering their names, aggregations, and data types. As a result, you will be able to alter it to suit your company’s goals.

    Looker:

    LookML is a language that can describe aggregates, dimensions, data relationships, and calculations. LookML is capable of constructing SQL queries against a database. Looker has 100+ pre-built modeling patterns that run with LookML.

     

    Analytics

                Data Studio:

    When it comes to analytics, Google Data Studio does not have advanced capabilities. Because of this, Google Data Studio does not fit with advanced uses like predations and forecasts. This is one of the most significant differences between Google Data Studio vs Looker.

    Looker:

    On the other hand, with Looker you can install various machine learning models from its marketplace. These models can be used for regression, classification, and forecasting. After successfully applying a machine learning model, the produced results can be used with platforms such as Google Analytics.

     

    Price

                 Data Studio:

    Looker Data Studio is a completely free tool. All you need is a Google account

    Looker:

    Looker is an enterprise-grade tool that has a trial version. For ten users, Looker will cost you around $3000 to $5000. Even though this is an expensive tool, we think your investment won’t go to waste.

     

    Conclusion:

    Google offers two products that provide collaborative dashboards and visualizations – Data Studio and Looker. Although their functions overlap in many ways, there are key differences between them; for instance, Data Studio satisfies basic BI needs while Looker is designed to offer a centralized source of truth for enterprises with advanced data models & machine learning capabilities built-in. Plus it can serve as a CDP offering the ability to create complete customer profiles from online/offline sources.

    Looker, gives users the power to manipulate their data like never before and seamlessly import it into platforms such as Analytics 360. The ability to work with LookML for schemas and modeling is an attractive feature; however, this tool isn’t suited for everyone due to its price tag and technical requirements in SQL knowledge. If you have advanced use cases that require more than just basic analytics capabilities though – Looker may be your go-to choice.

    If you need assistance with Looker, Data Studio or collaborative dashboards and visualizations in general, please reach out to the experts at Napkyn. 

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