Salesforce’s acquisition of Tableau intensified competition in the BI software market. At the same time, Google acquired Looker, positioning it to compete with Azure and AWS in the cloud.

Our analysts broke down the Looker vs. Tableau comparison with an apples-to-apples comparison. Tableau won, hands down. Let’s dive into the details

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Article Roadmap

• Feature Comparison
  • Dashboarding and Data Visualization
  • Reporting
  • Advanced Analytics
  • Embedded Analytics
  • Augmented Analytics
  • Data Management
  • Data Querying
  • Geospatial Visualizations and Analysis
• Which BI Tool Wins?
• FAQs
• Next Steps

Looker vs. Tableau Overview

When Google set out to acquire Looker, it was already an established BI tool with powerful data modeling and interactive dashboards with drag-and-drop capabilities.

With this coup, Google planned to offer a product that would compete with Azure and AWS offerings in the cloud. Looker is, after all, cloud-based.

Tableau has always marketed itself as a data visualization tool. Salesforce bought it to augment its analytics offerings for this very purpose. Now, Tableau is stronger than ever with AI/ML in its arsenal.

Feature Comparison

Now that Looker belongs to Google, they both have something better to offer. Google has a friendly data exploration interface that presents data from Google BigQuery and CloudSQL. And Looker gains the versatility to work with big data, whatever the type.

While Looker has LookML, Tableau relies on SQL and a visual query language. The following table gives a bird’s eye view of the Tableau vs. Looker comparison.

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Dashboarding and Data Visualization

Looker gives you a head start with readymade charts and graphs. You can also create your own and show data changes over time using an animation plugin.

Dashboards update automatically with the latest data. You can add new details, reorder information and remove fields to focus only on the desired data. Zoom in for a closer look, or use tooltips for closer explanations.

Looker can automatically generate charts as you drill down for deeper insights.

Explore location metrics with zooming maps and scaling features.

Farid Asadi, Conversion and Experimentation Manager at SelectHub, shared his experience with Looker.

Since its beta release, I’ve been using Looker to design dashboards for a broad range of brands. My aim is to concentrate on the metrics that truly matter, presenting them in a clear and accessible way through thoughtful data visualization. It’s my belief that effective dashboards should be focused, highlighting key metrics that need regular attention while also allowing for easy access to more detailed data as needed.

This approach stems from the idea that trying to display every possible metric can actually hinder our ability to uncover deeper, more meaningful insights. Instead, I use Looker to focus on the most critical goals and integrate various data sources into a single, streamlined page.”

Tableau provides stunning visualizations that go beyond static charts and graphs. Embed dashboards directly into web pages, applications, blogs and wikis. Use robust statistics and unique chart types using Python/R scripts.

Find the perfect chart type for your data with the Show Me feature. Drill down for details, filter data, highlight specific areas and use tooltips for deeper explorations. Make dashboards your own with your logos, colors and fonts.

Reporting

Looker offers decision support by letting you create and share reports across your organization. The free version is available with your Google workspace, so signed-in team members can access reports using a shared URL.

Anyone can create reports using its friendly interface, field picker and handy filters. Reports are interactive and allow drilling down and filtering to explore data further. The option to set up object-level security allows for restricting data access.

Keep everyone on the same page by sending them reports via email or scheduling them to go out at regular intervals. You can set up reports to trigger when certain events happen.

Tableau supports ad hoc reporting, but there’s a process to it. First, you must publish the data on the Tableau Server and create a sample workbook, provided you have editor permissions.

Users can sign up to receive an image or PDF snapshot of a Tableau view or workbook via email. Versioning is built-in, and the Ask Data module makes text searches possible.

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Advanced Analytics

With Looker, you can create custom fields and perform calculations on the spot. You can group similar data points and analyze them together using cluster analysis.

Track trends over time using time series analysis and moving averages. Understand the relationship between data points using regression.

A Tableau vs. Looker comparison must include Google BigQuery. It’s a data warehouse that serves as a catch-all for all your data, including unstructured data. Google offers pre-built data models called Looker Blocks to help you hit the ground running.

Tableau has kept pace with BI trends, going beyond basic data visualization to provide advanced analytics. Explore time series with its built-in date and time functions or create forecasts using Python, R and MATLAB.

You can perform key driver analysis by grouping data and building custom calculations with formulas. Tableau offers basic text processing.

Embedded Analytics

Looker lets you embed data, charts and dashboards into applications. You can drill down and explore data, schedule alerts and ask questions. The platform can support over 100 tenants. Secure write-backs are available.

You can filter a product list in a Looker dashboard embedded within a sales application. Or, by clicking on a customer’s ID within a Looker visualization, populate a support ticket with details for that customer.

LookML is the core data modeling language and plays a crucial role in how users embed and access Looker content.

In contrast to Looker, Tableau has embeddable dashboards that you can publish on the web. Web-based interfaces enable the exploration of data and the creation of presentations independently. Tableau has always advocated self-service BI.

A single Tableau instance can have separate workspaces with private projects and tasks. All workspaces can share data from the Tableau Server, and admins can set up access permissions at the project level.

Tableau can scale to perform tasks in parallel if the workloads are heavy. White labeling and task automation are available. You can write back to the database, though it might require custom development.

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Augmented Analytics

Augmented analytics uses AI and machine learning to uncover helpful insight. It involves automating repetitive tasks to save time while getting the work done.

It closes the gap between non-technical users and data by letting them ask simple English questions like “What are the top sales trends this quarter?”

Looker serves as a friendly interface for users as BigQuery machine learning trains and runs data models at the back.

The platform lets you derive insight by grouping similar datasets based on certain similarities. Looker offers automatic recommendations and text querying.

Have you ever wondered why a specific data point is high or low? Tableau’s Explain Data button is like having a built-in analyst. Click it, and Tableau highlights the most critical factors influencing that data point.

In contrast to Looker, Tableau has a built-in Ask Data feature that lets you ask data questions in plain English.

Want to see trends, comparisons or details about specific data points? Type your question, and Tableau will generate clear explanations and visualizations.

It’s beneficial for people who aren’t comfortable writing complex queries. It saves time and lets users explore data freely.

Data Management

Efficient data management will keep analysis complete, accurate and free of errors. It avoids having multiple entries for the same data and organizes information in a way that makes sense.

Finn Wheatley, Executive Consultant of Data & Technology at Xtrium, stressed on the importance of data quality.

Companies can ensure that their data is accurate and consistent by implementing best practices in data management, such as standardization and data quality controls.”

Data governance enforces business rules for secure data access, but it’s easier said than done.

Wheatley shared that lack of ownership was a common blocker.

My pet peeve regarding data governance is when organizations fail to establish clear ownership and accountability for their data, leading to confusion and data silos within the company.”

For data security, Looker uses single sign-on (SSO) to manage user access. Plus, it uses an API to control who sees what data.

LookML helps you connect different pieces of data, like building blocks. You can also define custom calculations to transform your data for analysis.

Looker lets you mix data from various sources, like ingredients in a recipe. Unlike Tableau, Looker uses persistent derived tables (PDTs) to handle this combining process. However, for very complex tasks, you might need other tools.

Tableau Prep effortlessly merges data from multiple sources. Before diving into analysis, the Prep module scrubs your data free of errors and inconsistencies. Pivot tables, custom fields and filters help reshape your data.

Once the data is ready, Tableau lets you analyze any data type by creating stunning dashboards and visualizations. It helps you make informed decisions by giving you a clear understanding of insight.

Data Querying

Looker shows you the latest data thanks to its live connection to Amazon Redshift, Snowflake and Vertica. While it doesn’t analyze data in memory, it can cache commonly used data for faster performance.

Looker has something for everyone — a visual query builder for non-technical users and SQL code for power users. A Bulk Find and Replace feature lets you apply the same changes across a large dataset.

Tableau is capable of handling large volumes while connecting to databases. It can break down tasks into manageable portions and assign them to nodes that work side-by-side. It’s called parallel processing.

When handling large volumes, Tableau can add cores to increase its processing power. You can drag and drop datasets to derive information using a visual query builder.

Unlike Looker, Tableau analyzes data in memory, serving it faster when needed. This makes it more efficient for complex calculations.

Geospatial Visualizations and Analysis

Looker uses Vertica’s geospatial functions, scalability and robust performance. Mapbox, Bing Maps and Google Maps integrations let you zoom in, explore and gain a richer understanding of your data.

Looker supports the TopoJSON format, a popular way to define map layers. It lets you create custom visualizations and highlight specific areas or data points.

Which are the most profitable locations to open new stores? How do sales trends vary across regions? Which delivery routes are the best? Looker can help you answer these and many more such questions.

Tableau offers many functions to create location-based views, including MakeLine, MakePoint and Distance. You can quickly locate data points using addresses, coordinates, and map searches and choose from various views to display data.

Unlike Looker, Tableau can pull maps from the web. It lets you view data in the context of the real world.

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Which BI Tool Wins?

Tableau wins this comparison for seven out of eight features. The platform leads in dashboarding, augmented and embedded analytics, data management and querying, and reporting and location analytics.

This Tableau vs. Looker comparison also reveals some limitations of the two.

Tableau doesn’t have a free edition. Plus, there’s a learning curve. Tableau Prep can be a boon or a complexity, depending on how you look at it. It’s a separate download, and you need a Tableau Creator license to access it.

Looker Studio (formerly Data Studio) is free and easy to use, offering a low entry point for data explorers. Integration with Google products is a definite plus.

But, there aren’t many ways you can customize data views, and Looker isn’t available offline.

FAQs

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Next Steps

Want to learn about other BI products? Get our free comparison report to evaluate up to five BI products at a glance, with clear rankings based on features and functionalities.

What are your takeaways from this Looker vs. Tableau comparison? Let us know in the comments.

SME Contributors

Finn Wheatley started in London finance as a risk manager and investment analyst and transitioned to data science with a Master’s in Computer Science (UCL). He now consults for major corporations, implementing advanced analytics and solving tech issues.

Farid Asadi is the Conversion & Experimentation Manager at SelectHub and designs growth and conversion optimization programs that turn hypotheses into cash flow. He writes about conversion optimization, analytics, metrics and experiments.