Differences between Tableau Vs Looker-2021

Data is the backbone of business operations. Many companies have realized the power of data and started investing in data visualization tools to understand their data that drive positive business outcomes. While there are several data visualization tools available out there, each with varying features, it becomes difficult to choose the best among them for your business.

In this Tableau vs Looker blog, we'll compare the two popular data visualization tools based on various parameters that help you decide which one is best suited for you.

But, before getting into comparing, let's have a quick introduction to both these tools.

Looker:

Looker Data Platform is a data discovery platform that helps businesses make better business decisions by accessing data in real time. Regardless of the size, the data can be analyzed in Looker's 100% database and browser-based platform. Looker Analytics integrates with any SQL database or data warehouse, such as Amazon Athena, Greenplum, and Microsoft Azure SQL Data Warehouse.

Tableau:

Tableau offers powerful BI tools that improve information disclosure and understanding for a wide range of business and customer affiliations.. With a simple drag-and-drop functionality, users easily analyze key data, share critical information across the enterprise, and create innovative visualizations and reports. Additionally, Tableau offers the ability to integrate .

Key differences between Tableau vs Looker:

Tableau	Looker
1.In Tableau, users can easily analyze data and create reports using drag and drop options.	1. In Looker, users can easily drag-and-drop reports and assign roles such as developers, users, and administrators to efficiently analyze data.
2.Tableau integrates with CSV, spreadsheets, spreadsheets, SQL databases, Google Analytics and many more	2.Looker integrates with third party apps like Green plum and Amazon Athena etc.
3.Tableau has snowflake models and dimensional data to help improve analytical queries.	3.Looker has a LookML data model that is reusable and provides sophisticated tools for creating high-level analyzes.
4.Tableau is compatible with Windows and Mac operating systems.	4.Looker is also compatible with Windows, Mac and Linux operating systems.
5.Tableau has a mobile web app that supports devices like Android and iOS.	5.Looker is accessible from any browser on mobile devices connected to the web.
6.With Tableau, users can create custom reports based on user needs.	6.Looker has standard templates that allow users to create reports quickly and efficiently.
7.Tableau keeps your data secure at every level.	7.In Looker, users should change security settings according to user needs.

Data visualization:

Data visualization comes in many forms, such as charts, graphs, dashboards, spreadsheets, widgets, infographics, heat maps, tree maps, and funnels.

Tableau: Tableau is a powerful BI tool used for data visualization. Data analysis can be done quickly and efficiently with Tableau. You can create data visualizations in the form of dashboards, charts, and spreadsheets. Tableau has ready-made templates; so that you can easily prepare dashboards by drag and drop. It allows the user to create images and graphics without the help of any programmer. Any professional can understand the data created with Tableau.

Looker: Looker is also a BI tool used for data visualization. Looker allows you to create and configure charts and graphs by drag and drop. You can also enter the desired items and assign roles such as users, developers and administrators. Looker Training makes you get Expertise with Looker BI Reports & Big Data Analytics.

The integration:

Tableau: Tableau integrates with a wide range of data sources such as CSV, spreadsheets, SQL databases, Google Analytics, and many more. It also connects to the R to provide control to analytical tools.

Looker: Looker with SQL databases is an open API to integrate and third party applications like Green plum, Amazon Athena, etc.

Data Modeling

Tableau: These models are used in a data warehouse to integrate data with different sources and help improve the performance of analytical queries.

Looker: Looker provides a powerful, reusable and flexible LookML data model. LookML replaces SQL because SQL is neither reusable nor flexible. Therefore, LookML provides sophisticated tools for analysts to create high-level analysis.

Reporting:

Table: Table is the best tool for creating reports. You can prepare custom reports based on user needs. Tableau utilizes broad connectors and a quick composing climate to make and distribute dashboards and reports in an assortment of yield designs.

Looker: Looker provides the user with standard report templates. Looker allows Ad Hoc Reports to create custom reports based on user specifications.

Speed:

Tableau: Tableau enables users to create effective interactive visualization reports in minutes. It can make the whole process faster and easier by allowing you to share reports online and offline.
Looker: Looker takes a long time to process data and create reports against Tableau. Sharing reports with you takes hours

Security:

Tableau: Tableau keeps your data secure at every level. You can protect reports, dashboards, and spreadsheets whenever you want to protect them. You can grant permissions to specific users to whom you want to give access to reports.
Looker: Looker has a section in the admin panel to change security settings, such as two-factor authentication, Google and HDAP authentication, and HTML disinfection

Operating System:

Tableau: Tableau is compatible with Windows and Mac operating systems.

Looker: Looker is also compatible with Windows, Mac and Linux operating systems.

Mobile assistance:

Tableau: Tableau has a mobile web app that supports devices like Android and iOS.

Looker: Looker is accessible from any browser on mobile devices connected to the web.

Prices:

Tableau Pricing: Tableau offers several subscription plans for users. The price varies depending on the distribution and version. Tableau offers a free trial version.

Looker Pricing: Looker also offers a different type of subscription plans to users

Online Analytical Processing (OLAP):

Online analytics processing through Tableau allows users to extract data for deep analysis. The data is organized in a predefined cube format where it overlaps: Examples of OLAP cubes supported by Tableau are Oracle Essbase, Teradata OLAP, Microsoft Analysis Services, SAP NetWeaver Business Warehouse, Microsoft Power Pivot, and analytical views in SAP Hana. OLAP functions available in Tableau include data mining, extraction, filtering, and automatic time series generation. However, the default nature of OLAP cubes limits the functionality of some features, such as data grouping.
Tableau is better than its competitor in this category because it works with OLAP cubes and Looker with OLAP. Looker aims to replace traditional OLAP functionality with its own deep data navigation methods. If your business needs OLAP, Tableau is the right choice.

Decision Services

The counseling administrations given by Looker assist the clients to comprehend the usefulness of the framework with the assistance of Looker specialists. Looker offers software training and workshops, as well as on-demand customer service.

Tableau's analytics capabilities provide insight into business performance that can be used in future decision making. If you need help interpreting the scans, this provider offers consulting services to help you with your planning. In addition, Tableau provides fraud detection tools for users. The decision-making services offered by Looker and Tableau provide users with a resource to learn more about systems and take full advantage of the tools they provide, placing systems in a model for this category. These services help small businesses without in-house analytics experts reap the benefits of BI just as much as large businesses.

Conclusion:

To conclude in a comparison between Looker and Tableau, Tableau appears to be the superior business intelligence system to Looker. Based on the capabilities assessed above, Tableau has the upper hand in several categories of requirements: data visualization, inline analytics processing, and big data integration.

Author Bio:

I'm Srija Kalavala, a fascinated Technical Content writer currently working at Mindmajix. Interested to know about technology updates. I Can write an article on the following technologies Database Management, Cloud Computing, Business Intelligence and Analytics, Cyber Security and SIEM Tools, etc. Get connected with me on Linkedin.