Looker vs Tableau: Differences and Use Cases Explained

Looker and Tableau are popular business intelligence (BI) tools. Whether you want to visualise a data set or build complex dashboards, these two data analytics platforms have you covered. 

When choosing a tool, consider factors such as your business goals, the types of data you use, and your current integrations, as well as costs and specific features.

Explore the features, pricing, and use cases of Looker and Tableau, giving you a clear understanding of how the platforms differ and which platform is best for your business. Discover suggested cost-effective courses to help you gain job-relevant data visualisation skills today. 

Looker vs Tableau

Looker and Tableau have a lot in common but have some key differences that might impact your choice. Here are some key differences and similarities to consider. 

What is Looker? 

Looker is a data visualisation tool part of Google’s Cloud Platform (GCP), which includes a large suite of interrelated tools like BigQuery, Cloud Storage, and CloudSQL. Organisations use Looker to create dashboards and reports that transform data into easy-to-understand graphs and charts, gaining actionable insights and making informed, data-driven decisions. 

Looker uses its own dependency language, Looker Modeling Language (LookML), which builds around Structured Query Language (SQL) to create semantic data models. This makes LookML relatively easy for data professionals with SQL experience to learn. It also allows technical users like data engineers to create bespoke data models that act like simple-to-use applications for the many non-technical Looker users who must reference data daily in their roles.  

Looker pricing varies based on the number of connected data sources, users, and scale of deployment. But, the technology doesn’t come cheap. Most outlets report that a Looker subscription costs around 35,000 USD a year and can easily go higher, depending on an organisation’s particular needs. 

Looker features 

Looker is a powerful business intelligence tool that empowers both high-level executives and on-the-ground employees to make more informed business decisions. Some of Looker’s key features include: 

• Integrated platform: The Looker platform seamlessly integrates into pre-existing BI solutions, allowing business teams to incorporate them into their already established workflows easily.

• LookML: The Looker Modeling Language (LookML) allows data professionals to create custom applications and tools based on users’ needs.

• Looker Blocks: Looker allows users to use pre-built pieces of code called “blocks,” ranging from fully developed data models to custom visualisations. Looker users can search Looker Marketplace for different “blocks” to integrate into their data analytics platform. 

• Embedded analytics: Looker includes embedded data analysis tools that provide users with real-time data and actionable insights. 

• Version control: Looker is unique because it provides version control, so users know what changes are made, by whom, and for what reason. 

Looker use cases

Lookers are primarily used by businesses to create data visualisations. For example, a business might use Looker to transform its sales data into a series of graphs, charts, and maps that illustrate the fluctuations of its quarterly sales throughout the year, break down the different types of products it sells, and highlight the different regions where buyers were. 

Looker’s design intends to be scalable to grow with an organisation. This allows companies to retain Looker as a BI tool rather than making the costly decision to change their workflow and architect a new solution once they’ve increased their footprint. 

What is Tableau? 

Tableau is a data visualisation tool used to create dashboards and reports based on an organisation’s various data sources. It includes a desktop application (Tableau Desktop) that can be published to other users via a dedicated server (Tableau Server) or through the cloud (Tableau Cloud).  

Tableau is a well-regarded BI tool because users can easily create visualisations by dragging and dropping pre-existing data fields into a sheet. The platform can interpret a data set and break it down into different dimensions and measurements, including already existing ones and those generated by the application. This makes Tableau simple for non-technical users to both gain insights from data and share them with others.  

Tableau pricing varies based on the number and type of platform users. Tableau breaks down users into three types that each have their own monthly cost: Tableau Creators cost 75 USD per user each month; Tableau Explorers cost 42 USD per user each month; and Tableau Viewers cost 15 USD per user each month. Each of these different types of users can perform different tasks on the platform, ranging from using the full spectrum of the platform’s capabilities (Creators) to those who can only view pre-existing visualisations (Viewers). 

Tableau features 

Tableau offers one of the easiest-to-use data visualisation platforms on the market. Some of Tableau’s key features include: 

• Integrated platform: Tableau can work on-premises, in the cloud, or natively integrated within the Salesforce CRM. You can also embed it online or within Slack. 

• Data analytics: Tableau users can build visualisations, employ AI-driven statistical modelling, and even use natural language to ask the platform questions. The software also allows for real-time analytics so users have updated information at their fingertips. 

• Ease of Use: Compared to some more involved BI tools, Tableau is generally considered an easy-to-use platform that allows users to create visualisations without prior experience working with data.

• Sharing and collaboration: Tableau equips users to easily share their insights with their colleagues by simply publishing on their shared server or via the cloud. Mobile applications also allow users to access this material more easily. 

Tableau use cases

Like Looker, you can use Tableau to create visualisations, dashboards, and reports so that businesses can make more informed, data-driven decisions. For example, an SEO marketing team might use Tableau to create graphs illustrating the number of monthly site visitors to demonstrate traffic growth since starting the most recent marketing campaign. 

Tableau shines through its ease of use, which allows non-technical users to create visualisations and convey their findings. This is particularly helpful to businesses that need to develop a data-driven culture but lack a fully developed data team to create and manage their data operations. Tableau is also scalable and can grow alongside businesses.  

Should you use Looker or Tableau? 

Looker and Tableau are powerful data visualisation and analytics platforms that can provide organisations with the insights they need to make smart business decisions. So, how do you decide which is the right one for your business? You’ll find many answers to this question. As a result, when deciding between Looker and Tableau, it’s important to consider the following: 

• Price

• Your use cases

• The size of your existing data team 

As a rule, Tableau will be the cheaper option for smaller organisations because they’ll pay a variable rate based on the number and type of users. Tableau is also a good option for organisations with smaller data teams because it's easy to use for non-technical users. It’s important to note that the price can increase significantly as you add more and more users to the account. 

Looker, on the other hand, will likely be more cost-effective for larger organisations with a large number of users who will need to reference the platform routinely. It’s also a good option for organisations with a developed data team who can create bespoke dashboards for non-technical users through the use of LookML. At the same time, it’s important to recognise that Looker can be expensive for smaller organisations. 

If you’d like to find out more about the exact price you’ll pay for both solutions, reach out to their respective support teams to learn more so that you can know the exact amount each platform will cost you. 

Learn more about data with Coursera. 

BI tools like Looker and Tableau empower users to make better, more informed daily decisions. To expand your BI and analytics capabilities, consider earning a Professional Certificate through Coursera to gain job-relevant skills today. 

In the Google Business Intelligence Professional Certificate, on Coursera, you’ll have the opportunity to learn in-demand skills like data modelling, data visualisation, dashboarding, and reporting in less than two months. For those looking to learn more about data, meanwhile, the Google Data Analytics Professional Certificate, also available on Coursera, teaches key analytical skills like data cleaning, analysis, and visualisation, and tools like spreadsheets, SQL, and Tableau.

professional certificate

Google Business Intelligence

Learn in-demand skills like data modeling, data visualization, and dashboarding and reporting in less than 2 months.

4.8

(2,196 ratings)

106,782 already enrolled

Advanced level

Learn More

Average time: 2 month(s)

Learn at your own pace

Skills you'll build:

Business Intelligence, Extraction, Transformation And Loading (ETL), Bigquery, Dashboarding and Reporting, Data Analysis, Data Modeling, Business Analysis, SQL, Tableau Software, Business Process, Sheets, Data Visualization, Effective Communication, Presenting Data Insights, Data transformation, Data Management, Database Optimization, Google Dataflow/Google BigQuery, Business Processes and Requirements, Sharing Insights With Stakeholders, Stakeholder Management, Cross-Functional Team Dynamics, Asking Effective Questions

professional certificate

Google Data Analytics

Get on the fast track to a career in Data Analytics. In this certificate program, you’ll learn in-demand skills, and get AI training from Google experts. Learn at your own pace, no degree or experience required.

4.8

(151,564 ratings)

2,597,685 already enrolled

Beginner level

Learn More

Average time: 6 month(s)

Learn at your own pace

Skills you'll build:

Data Analysis, Creating case studies, Data Visualization, Data Cleansing, Developing a portfolio, Data Collection, Spreadsheet, Metadata, SQL, Data Ethics, Data Aggregation, Data Calculations, R Markdown, R Programming, Rstudio, Tableau Software, Presentation, Data Integrity, Sample Size Determination, Decision-Making, Problem Solving, Questioning