The Battle of Google’s Looker Products: Which One is Right for Your Data Visualization Needs?

Looker and Looker Studio (Pro), formerly known as Google Data Studio, are two widely used business intelligence tools of the Google cosmos that help creating interactive dashboards and reports. Both tools have their own strengths and are designed for different use cases and target groups. In this article, we explore the features of each tool and highlight their differences by describing typical use cases where they are best suited. We will also point out the most important advantages and disadvantages of the tools. At the end of this article, you will find a downloadable PDF file, summing up this comparison of Google’s BI tools.

 

Table of Contents

1. Looker

2. Looker Studio

3. Looker Studio Pro

4. Summary and Conclusion

 

1. Looker – The Ferrari among Business Intelligence Tools?

Use case 1: Re-gain trust in the data and introduce self-service analytics in a scale-up

A data-driven scale-up observed that their data team was becoming a bottleneck when generating analysis and providing insights as all the company’s dashboards needed to be built by data analysts using SQL queries. Additionally, the company experienced some inconsistencies in metrics displayed in different reports, leading to diminishing trust in the data. The company wants to implement a self-service approach to provide data directly to the hands of their business users who are already data-savvy while ensuring that metrics follow the same definitions across all reports.

In this example use case, Looker is a desirable tool to tackle the problem of inconsistent metrics and enable business users to generate insights using data on their own without any SQL knowledge.

Looker is a data platform that allows companies to connect to their data warehouse(s), explore their data, and create visualizations and dashboards on top of it. It offers a unique semantic layer using Looker’s own language called LookML, which describes dimensions, aggregates, calculations, and data relationships in a SQL database. LookML is a mix of YAML and dialect-independent SQL used to create reusable, version-controlled data models. Looker uses these models to generate SQL queries against the database. LookML fosters data analysts and analytics engineers to follow the DRY (“don’t repeat yourself”) software development principle. It means that you write SQL expressions once, in one place, and Looker’s query engine uses the code repeatedly to generate ad-hoc SQL queries. Business users can then use the results to build complex analyses and dashboards in Looker, focusing only on the content they need, not the complexities of the SQL behind it. By removing the burden of knowing SQL to do data analysis, the company made a big step to enable self-service analytics.

The dimensions (e.g., “what is a user?”) and metrics (e.g., “how is MRR defined?”) are only defined in one place, making them consistent across all reports, which restored trust in the data of business users.

 

Use case 2: A large retail company wants to analyse data from multiple sources

A large retail company wants to analyse data from various sources, including their online store and physical stores, to uncover growth areas and develop a greater understanding of customer behaviour. The company wants to provide performance overview dashboards to their store managers, where each manager can only access the data relevant to them. They also want to embed customized dashboards containing insights on performance of specific products and buying behaviour into their partner platform and charge their main partner brands for access.

In this second example use case, Looker is the ideal tool to use because it can connect to a variety of data warehouses in which the customer keeps the data from their different data sources, provides row- and column-based user access management capabilities and white-label dashboard embedding. Looker’s access control feature enables teams to share the data and visualizations with only the relevant people, making it perfect for this use case where store managers and partner brands using Looker should only be able to see the data related to them.

By using Looker’s retail analytics block the company saved hours of work otherwise spent on data modelling and dashboard creation. The block provides a comprehensive overview of the company’s group and store performance, their customer’s behaviour, basket dynamics, and which customer segments or product bundles to promote. Looker blocks are templates for data models and dashboards that ideally only need to be configured by the user to go from database to dashboard quickly. They consist of pre-built LookML code blocks that you can copy to your project. Looker blocks exist for a variety of data sources and use cases (e.g.,  Hubspot Marketing, Google Analytics 4, Shopify). But be aware that some blocks only work out-of-the-box when the data is available in a specific structure or optimized for a specific database. You can check out all existing blocks in Looker’s marketplace.

To make the created dashboards available to store managers and ensure they only have access to the data relevant to them, the company made use of Looker’s access control and permissions management features.

• They set up a “Store Manager” group to define content and feature for all store managers.
• “Content access” defines which folders can a user or a group of users view or edit whereas
• “feature access” controls the types of actions a user is allowed to do in Looker.
• In addition, they configured row-level access, so each store manager only has access to data related to the store they are managing.

To open a further revenue stream, they created a dashboard containing information about product performance and buying behaviour and embedded it in their partner portal. For a small fee, individual brands could use this analytical feature to support and accelerate market research and even product development. Looker offers embedding contents like dashboards via iframe in multiple secure ways like SSO embed or private embed. The company also made use of Looker’s possibility to create custom themes to ensure the dashboard fits nicely into the existing design of their partner portal.

Additionally, Looker also provides a built-in scheduling and alerting feature, which enables users to automate reports to be delivered to different teams or stakeholders on a schedule or whenever a certain condition is met (e.g., return rate increased a set value), which saves time and effort.

 

2. Looker Studio – A great fit for smaller companies

Having gained a comprehensive understanding of Looker’s capabilities, use cases, and features, we shall now shift our focus towards Looker Studio, formerly recognized as ‘Google Data Studio’. This user-friendly platform offers a lot of direct integrations, especially for Google products, simplifying the process of connecting with diverse data sources and deriving valuable insights. Its intuitive user interface allows users to perform self-service analytics by doing simple data modelling and building quick charts with basic features but not so much interactivity.

 

Use case 3: A startup wants to create simple, interactive dashboards to track the performance and growth of their product

A startup desires to track its sales and marketing performance following the introduction of its product on the market two years ago. They seek to generate streamlined, concise, and interactive reports for effective analysis of their sales and marketing channels. They require a tool that can be rapidly implemented and leveraged by non-technical users, as they lack significant IT resources. In this case, Looker Studio would be the optimal solution due to its user-friendliness, cost-effectiveness, and quick deployment, enabling non-technical users to gain valuable insights.

 

Looker Studio is a cloud-based data visualization solution, offered free of cost. Its drag-and-drop interface empowers non-technical users to design dashboards and reports, with pre-built charts, graphs, and tables. It’s simple to also create defined calculated fields for specific metrics per dashboard. Scheduled data refreshes can be set up at the report level to ensure that the information is always current. Creating report templates and the possibility of report embedding in web pages is also available.

Being a Google product, it seamlessly integrates with Google products as Google Sheets, Google Analytics, and BigQuery, and can also connect to popular platforms such as Salesforce and Facebook Ads – for all connectors offered you can check here. Data blending is also available to do basic data modelling as ‘left joins’ but for building a more complex data model, a data team would need to set up proper data pipelines and models in a data warehouse. The tool facilitates collaboration and sharing within organizations to a limited extent (e.g., no defined workspaces) but Looker Studio Pro, a new upgrade offering from Google, provides additional benefits and will be discussed in detail in the upcoming section.

 

As there is no perfect solution, one of the disadvantages of Looker Studio is that it has only limited data modelling capabilities and no version control. In case the startup grows and its requirements towards their BI tool increase (e.g., more in-depth analyses, more complex visualizations that offer more interactivity, better collaboration, advanced sharing capabilities and user permissions), Looker Studio may not be the best suitable tool. While it is free to use, some of the data connectors and data sources require additional costs. Also, Looker Studio has limited support for big data and may not be able to handle large data sets efficiently.

In conclusion, when it comes to data analysis and visualization for smaller operations, Looker Studio is the preferred solution due to its ease of use and cost-effectiveness. However, if a company is experiencing rapid growth and requires additional functionalities, Looker or Looker Studio Pro would be the more appropriate choice. It’s important to keep in mind that while Looker Studio has its limitations, it’s still a powerful tool that can be utilized to generate valuable insights and streamline data operations for small-to-medium-sized businesses. By selecting the right tool for your specific needs and being mindful of its strengths and weaknesses, you can effectively leverage data to make business-informed decisions.

 

3. Looker Studio Pro – The older brother of Looker Studio

Looker Studio Pro is a comprehensive tool that builds on the functionality and user-friendly interface of Looker Studio. Looker Studio Pro comes equipped with an array of additional features targeted towards enterprise businesses, such as

• the ability to define workspaces,
• set user management permissions and roles,
• and gain access to enhanced customer support through the Google customer care program.

The subscription model is estimated to be approximately $7 per user per month, subject to customization based on your specific business needs. To obtain a personalized pricing plan, we recommend contacting the Google sales team.

Use case 4: A mid-sized company that wants to create separate dashboards for each department

A mid-sized company is seeking to create distinct internal dashboards to monitor each department’s performance while ensuring ease of use, efficiency, and catering to non-technical users. To accomplish this, each department requires its own workspace, with defined permissions and user roles to control who can access, create, view, or edit reports. In this instance, Looker Studio Pro’s recently added features prove to be an ideal solution. With the ability to define team spaces, set user management permissions and roles, and access Google’s customer care program, Looker Studio Pro empowers users to streamline data operations while ensuring efficient collaboration and optimized performance.

One of the most significant advantages of Looker Studio Pro is its ability to create separate workspaces, enabling users to define individual or group-level access permissions for each workspace. In addition, Looker Studio Pro provides a variety of workspace roles, including manager, content manager, and contributor, to further enhance collaboration and control over data access – for more details about the roles check here. Notably, Looker Studio Pro eliminates the need to transfer ownership of reports when employees leave the company which is still a necessity with Looker Studio, saving valuable time and resources for businesses.

 

Furthermore, granting permissions to view or modify assets within the organization can be accomplished through Identity and Access Management (IAM) in the Google Cloud Platform (GCP).

 

Google is currently offering private access to bring Looker Studio content to Dataplex. Dataplex is an intelligent data fabric that empowers organizations to effectively locate, handle, oversee, and regulate their data across various data repositories such as data lakes, data warehouses, and data marts. This results in reliable control and enables large-scale data analysis, ensuring that data can be accessed with precision and accuracy.

Looker Studio Pro is a more advanced version of Looker Studio that comes with extra features, but still cheaper than Looker. This makes it a great option for medium-to-large sized companies that were missing enterprise access, permission and security features without breaking the bank.

 

Summary and Conclusion

In conclusion, Looker and Looker Studio (Pro) are all powerful data visualization tools, but they are designed for different use cases and targeted towards different customers.

Looker is widely considered to be one of the best BI solutions on the market, despite the existence of other promising tools (like Metabase, ThoughtSpot or Lightdash). Looker is best suited for companies that have large amounts of data, potentially stored in various databases and need a tool that can connect to all of them, clean, transform, and integrate data and create customized visualizations. It offers a powerful semantic layer for governing reusable metric and entity definitions, version control, scheduling and alerting, embedding into websites and applications, an API as well as extensive user and access management capabilities. Additionally, it is well integrated into the Google ecosystem, making it compatible with a variety of other Google products (like BigQuery). However, the cost of using Looker can be high, with monthly expenses reaching thousands of dollars, depending on the multiple factors like number and type of licenses needed and how it is deployed (self-hosted, hosted by Looker or Google Cloud core hosted). Other smaller downsides we see are limited visualization capabilities compared to Tableau (Looker does allow developing your own visualizations using Javascript, but that needs additional development resources). And that there is a bit of a learning curve when it comes to LookML. It is also worth noting that Looker is not meant for one-off analysis or exploratory work on new datasets, because the required dimensions and measures need to be modelled in LookML first. Additionally, since its acquisition by Google in February 2020, the quality of customer support has decreased, with fewer and less experienced people available to assist users. On the other hand, Google has increased their efforts of integrating Looker better into their existing product portfolio. With the recent announcement of “Looker Modeler”, Google is carving out Looker’s semantic layer as a stand-alone product and opens it up to other BI tools and applications.

Looker Studio is an excellent option for smaller sized businesses seeking to create simple, interactive dashboards and reports without breaking the bank or requiring extensive IT and data resources. It’s also ideal for individual analysis, one-off visualizations, and reports. Looker Studio can seamlessly handle a single data source, pre-aggregated datasets, spreadsheet data, and CSV files. While Looker Studio offers a vast range of native connectors, some may require an additional fee.

For those seeking greater control over user spaces, permissions, roles, and collaboration also through GCP, upgrading to Looker Studio Pro is an excellent option for a modest fee. Plus, with the Google Customer Care program, customers can expect exceptional support. Service-level agreements are also made available for the Pro version, which makes it a good option for enterprises.

As you now know, each tool has its unique strengths and limitations, and selecting the appropriate tool depends on your company’s particular requirements and use cases.

 

To help you match the strength and drawbacks of Google’s BI tools with your requirements and evaluate the best fitting solution for your company, you can find a structured summary of the tool comparison – ready to download – here:

Download full PDF overview

 

Do you have questions about Looker or Looker Studio (Pro), need support with choosing and implementing the right data architecture for your business or extracting data from your 3rd party tools and production databases into your data warehouse? Feel free to contact us via contact@feld-m.de – our experts will be happy to help you with advice, action and their experience!

You can find out more about our Data Product Services here.

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Additional resources

Looker

• https://connect.looker.com/library/video/why-use-looker
• https://www.looker.com/
• https://cloud.google.com/looker#all-features
• https://marketplace.looker.com/marketplace/directory
• https://cloud.google.com/looker/docs

Looker Studio

• https://support.google.com/looker-studio/answer/11521624?hl=en#jan-19-2023
• https://cloud.google.com/looker-studio
• https://cloud.google.com/dataplex
• https://lookerstudio.google.com/data

Looker Studio Pro

• https://cloud.google.com/blog/products/data-analytics/looker-next-evolution-business-intelligence-data-studio
• https://cloud.google.com/blog/products/data-analytics/an-introduction-to-looker-studio-pro
• https://support.google.com/looker-studio/answer/12791815?sjid=16168596214758561254-EU

 

Original photo by Charlesdeluvio on Unsplash