Looker and Tableau are two leading business intelligence and data analysis applications. Both offer a remarkable range of powerful features and capabilities, including strong data ingestion, sophisticated dashboards, rich data visualizations, and industry-leading features that leverage machine learning (ML).
Additionally, Looker and Tableau are highly rated by user communities, including in key areas such as security and access controls, quality of technical support, and strength of the peer user community.
Still, 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 your goals are, and what each of these packages offers. With that in mind, here’s an overview of Looker and Tableau’s strengths, weaknesses, and potential use cases.
See also: Best data analysis tools
Looker vs Tableau: Key Features Comparison
Which makes Picture the ability to visualize a rich and diverse range of data visualizations is so appealing to many businesses.
The platform offers unparalleled flexibility along with advanced tools to handle almost any type of data and any level of complexity, across any industry. Visualizations are presented through a desktop application as charts, graphs, infographics, heatmaps, clusters, and many other representations.
Images are easy to edit, adjust and adapt as trends change. Although the platform is ideal for data scientists and more technical users, it is quite easy to use for business users. Tableau has an edge over Looker in areas like interactive visual exploration and analytics dashboards.
the look The BI platform, now part of Google Cloud, offers sophisticated yet user-friendly drag-and-drop data modeling, although the app tends to focus more on the needs of IT teams and BI analysts.
Cloud-only Looker pulls data from a centralized, dedicated database, providing real-time visibility and a single source of truth. The solution provides a visually appealing and flexible dashboard (Looks) that connects to many data sources and cloud infrastructures. It offers a rich set of highly adaptable and engaging visualizations for technical and business users, and it offers an extensive modeling language. Looker beats Tableau in two key categories: content creation and content consumption.
See also: Main data visualization tools
Looker vs Tableau: Comparing Data Integration and Modeling
the Picture provides native collectors for a wide range of sources and applications, including Microsoft Excel, SQL Server, Google BigQuery, Snowflake, SAP HANA, Salesforce, Splunk, and Amazon Redshift. Yet, it can also extract data from Dropbox, Box, Google Drive, OneDrive and many other file and data storage repositories.
As part of Salesforce, Tableau provides integrated BI with the popular CRM platform. It also integrates with Slack. There are data science integrations, dashboard app integrations, and built-in analytics capabilities that can be linked to web portals and customer-facing products.
Additionally, 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 desktop computers as well as iOS and Android mobile devices. It offers highly rated apps, including one for CRM.
A clear advantage of look is that it is related to Google products, including BigQuery. However, with a rich and open set of native APIs and connectors, Looker pulls data from any SQL database as well as popular platforms and applications such as Magento, GSuite, LinkedIn, Shopify, ADP, Snowflake and Zendesk. It also allows connections through third-party apps such as Green Plum and Amazon Athena.
Data modeling is based on LookML, a machine learning framework that offers powerful functionality and a flexible framework for analysis. LookML includes over 100 predefined modeling templates called Looker Blocks.
The Looker platform can intelligently analyze and discover data, then infer relationships between tables in a schema to automate model building. Looker offers a mobile app for iOS and Android. Only downside: the product can present some difficulties for those who are used 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.
See also: Main data modeling tools
Looker vs Tableau: Performance Comparison
Part of the call of Picture is that it uses system resources efficiently. It does not push the limits of system memory and relatively quickly processes large volumes of data.
Users are attracted to Tableau for several other reasons: it offers great functionality, the software supports large and varied data volumes, it works well with a large number of concurrent users, and it integrates with virtually any infrastructure, including Windows and Mac. Tableau scores slightly higher than Looker in categories such as reporting and data sharing.
the look the platform receives quite high marks among users for functionality and overall performance. It works on Windows, Mac and Linux systems. It integrates well with other business software, including various analysis tools.
Looker generally uses system resources efficiently, although some users complain about data load times and the speed of processing very large data sets. There are also a few complaints about bugs in the dashboard and other parts of the app. One area where Looker easily beats Tableau is in the cloud BI space. Since the application is cloud-native and purpose-built for cloud processing, it provides a more flexible environment for cloud-centric organizations.
See also: What is Data Mining?
Looker vs Tableau: Security and Governance Comparison
the Picture The BI platform receives relatively high marks for its security and usability administration framework. Tableau offers an extensive collection of tools and features designed to simplify account security and administration. These include control over authentication methods, various filters, and restrictions on the availability of row-level security.
Additionally, the platform offers sandboxed extensions, network-enabled extensions, and a range of other protections, including encryption at rest. On the governance side, Tableau includes tools to define and manage data and content. It can adopt schemas based on Snowflake and Star, as well as more complex multi-fact models.
look user communities give the platform top marks for its security and governance framework. Looker incorporates Security Development Life Cycle (SDLC) principles, which include static and dynamic analyzes and in-depth code reviews.
Looker offers a wide choice of authentication methods, including 2FA, LDAP, Google OAuth, or SAML. It includes many database and user security management tools, including IP whitelisting, AES 256-bit data encryption as well as TLS 1.2 between database and browser, filters for template set and user attributes and various content security features. The latter includes the ability to make content fully open, open with content restrictions, and closed. The platform also offers strong governance features. It is HIPAA compliant and offers strong support for GDPR and other data regulations.
See also: Data Pipelines Guide
Looker vs Tableau: Services and Support Comparison
User communities report that Picture offers top notch service and support. The company receives high marks for the speed of responses and the quality of technical support. Additionally, more than 90% of Gartner Peer Review users say an additional support package they purchased was worth the price.
Customer support operates during standard business hours (8:00 a.m. to 5:00 p.m.), although customers have the option of purchasing extended support and premium support. The latter promises a 30-minute response and 24×7 critical phone support. Tableau offers a comprehensive 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 look 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 customer love department (DCL) does not operate a standard ticketing system; it heavily revolves around in-app chat and messaging for resolving issues. In contrast, the online Help Center offers comprehensive articles and documentation for development, APIs, administration, troubleshooting, and more. Users find the peer community valuable.
See also: Data Pipelines Guide
Looker vs Tableau: Price Comparison
A free trial version of Tableau is available. The price 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) costs $70 per month per user when billed annually.
Similarly, a free trial version of look is available. Looker offers subscription prices that depend on several factors, including the size of the organization. Typically, the license costs $300 per month per user up to 10 users, and $50 per month per user after 10 users.
See also: What is data analysis?
Looker vs Tableau: Ideal User Base
Both packages offer high-level BI capabilities and deliver broad and deep insights, rich visualizations, and powerful reports. Both BI solutions offer security, support, and large user communities. If your organization benefits from an extremely powerful and easy-to-use solution aimed at non-technical users, consider Picture.
If your business is more focused on a data science framework or a cloud-based framework that integrates Google (but extends to other services and applications), chances are you’ll find look more attractive.