Looker and Tableau are two premier business intelligence and data analytics applications. Both deliver a remarkable array of powerful features and capabilities, including strong data ingestion, sophisticated dashboards, rich data visualizations and leading-edge features that tap machine learning (ML).
In addition, both Looker and Tableau are highly rated by user communities, including in key areas such as security and access controls, the quality of technical support and the strength of the peer user community.
Yet there are key differences between the two platforms. As with any software, it’s important to understand how your organization consumes and processes data, what objectives you have and what each of these packages offers. With this in mind, here’s a look at the strengths, weaknesses and potential use cases for Looker and Tableau.
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Looker vs. Tableau: Key Feature Comparison
What makes Tableau so appealing for so many businesses is the ability to view a rich and varied array of data visualizations.
The platform offers unsurpassed flexibility along with advanced tools for handling almost any type of data and level of complexity, across industries. Visualizations are presented via a desktop app in the form of graphics, charts, infographics, heat maps, clusters and numerous other representations.
The images are easy to modify, adjust and adapt as trends change. While the platform is ideal for data scientists and more technical users, it’s easy enough for business users to use. Tableau has an edge over Looker in areas such as interactive visual exploration and analytics dashboards.
The Looker BI platform, now part of Google Cloud, delivers sophisticated yet user friendly drag-and-drop data modeling, though the application tends to focus more heavily on the needs of IT teams and BI analysts.
Cloud-only Looker pulls data from a centralized and dedicated database, and thus offers real-time visibility and a single source of truth. The solution provides a visually appealing and flexible dashboard (Looks) that connects to numerous data sources and cloud frameworks. It delivers a rich array of highly adaptable and attractive visualizations for technical and line-of-business users, and it offers an extensive modeling language. Looker prevails over Tableau in two key categories: content creation and consumption.
Also see: Top Data Visualization Tools
Looker vs. Tableau: Comparing Data Integration and Modeling
The Tableau solution delivers native collectors for a wide array of sources and applications, including Microsoft Excel, SQL Server, Google BigQuery, Snowflake, SAP HANA, Salesforce, Splunk and Amazon Redshift. Yet, it also can pull data from Dropbox, Box, Google Drive, OneDrive and many other file and data storage repositories.
As part of Salesforce, Tableau delivers integrated BI with the popular CRM platform. It also integrates with Slack. There are data science integrations, dashboard application integrations and embedded analytics capabilities that can be tied to web portals and customer-facing products.
In addition, the platform offers Snowflake and dimensional data models that connect to data warehouses and other repositories. This allows it to accommodate large volumes of data. Tableau is a clear winner for use on desktops as well as iOS and Android mobile devices. It offers highly rated apps, including one for CRM.
An obvious advantage of Looker is that it ties into Google products, including BigQuery. However, with a rich and open set of APIs and native connectors, Looker pulls data from any SQL database as well as popular platforms and applications like Magento, GSuite, LinkedIn, Shopify, ADP, Snowflake and Zendesk. It also allows connections through third party applications such as Green Plum and Amazon Athena.
Data modeling is based on LookML, a machine learning framework that delivers powerful features and a flexible framework for analytics. LookML includes more than 100 pre-built modeling patterns called Looker Blocks.
The Looker platform can intelligently scan and discover data and then infer relationships between tables in a scheme to automate model building. Looker offers a mobile app for iOS and Android. One downside: the product can present some challenges for those accustomed to working with OLAP cubes. Users must rely on a mobile browser. However, Looker wins out for self-service data preparation and the ability to embed analytics content.
Also see: Top Data Modeling Tools
Looker vs. Tableau: Performance Comparison
Part of the appeal of Tableau is that it uses system resources efficiently. It doesn’t push the limits of system memory and it processes large volumes of data relatively fast.
Users are attracted to Tableau for several other reasons: it delivers excellent functionality, the software supports large and diverse volumes of data, it operates well with a large number of concurrent users, and it integrates with virtually any infrastructure, including both Windows and Macs. Tableau rates slightly higher than Looker in categories such as report creation and data sharing.
The Looker platform receives fairly high marks among users for overall functionality and performance. It runs on Windows, Macs and Linux systems. It integrates well with other enterprise software, including various analytics tools.
Looker generally uses system resources efficiently, though some users complain about data load times and processing speed for ultra-large data sets. There are also some complaints about bugs within the dashboard and other parts of the application. One area in which Looker beats out Tableau handily is the cloud BI space. Since the application is cloud native and specifically designed for cloud processing it delivers a more flexible environment for cloud-centric organizations.
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Looker vs. Tableau: Comparing Security and Governance
The Tableau BI platform receives relatively high marks for its security and usage administration framework. Tableau provides an extensive collection of tools and features designed to simplify security and account administration. These include control over authentication methods, various filters, and restrictions on the availability of row-level security.
In addition, the platform offers sandboxed extensions, network-enabled extensions and an array of other protections, including encryption at rest. On the governance front, Tableau includes tools for defining and managing data and content. It can adopt schemas based on Snowflake and Star, along with more complex multi-fact models.
Looker user communities give the platform top ratings for its security and governance framework. Looker incorporates security development lifecycle principles (SDLC), which include static and dynamic scans and extensive code reviews.
Looker offers a wide choice of authentication methods, including 2FA, LDAP, Google OAuth, or SAML. It includes numerous tools for managing database and user security, including IP whitelisting, AES 256-bit data encryption along with TLS 1.2 between the database and the browser, filters for model-set security and user attributes and various content security features. The latter includes the ability to make content completely open, open with content restrictions, and closed. The platform also delivers strong governance features. It is HIPAA compliant, and it provides strong support for GDPR and other data regulations.
Also see: Guide to Data Pipelines
Looker vs. Tableau: Service and Support Comparison
User communities report that Tableau delivers top-notch service and support. The company receives high grades for timeliness of responses and quality of technical support. In addition, more than 90% of users at Gartner Peer Review says that an additional support package they purchased was worth the price.
Customer support operates during standard business hours (8 a.m. to 5 p.m.), though customers have the option of purchasing extended support and premium support. The latter promises a 30-minute reply and 24×7 mission critical phone support. Tableau offers an extensive online support site, with easy-to-find links for support, drivers and known issues. Users also find the quality of the peer user community valuable.
Because Looker is now part of Google, organizations using Google products, including BigQuery, will have a much easier time managing service and support in a consolidated way.
However, Looker has a somewhat idiosyncratic support framework. Its Department of Customer Love (DCL) doesn’t operate a standard ticketing system; it revolves heavily around in-app chat and messaging to address problems. On the upside, the online help center offers extensive articles and documentation for development, APIs, administration, troubleshooting and more. Users find the peer community valuable.
Also see: Guide to Data Pipelines
Looker vs. Tableau: Pricing Comparison
A free trial version of Tableau is available. Pricing varies depending on the specific product and how it is deployed. For example, Tableau Creator (which includes Tableau Desktop, Tableau Prep Builder and a single license for Tableau Server or Tableau Online) is $70 per month per user when billed annually.
Likewise, a free trial version of Looker is available. Looker offers subscription pricing that depends on several factors, including the size of the organization. Typically, licensing costs $300 per month per user for up to 10 users, and $50 per month per user after 10 users.
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Looker vs. Tableau: Ideal User Base
Both packages deliver top tier BI capabilities and deliver broad and deep insights, rich visualizations and powerful reporting. Both BI solutions offer strong security, support and large user communities. If your organization benefits from an extremely powerful and easy-to-use solution slanted toward non-technical users, consider Tableau.
If your business is focused more heavily on a data-science framework or cloud-based framework that incorporates Google (but extends outward to other services and applications) it’s likely you will find Looker more appealing.