Business intelligence and data analytics tools like Looker and Tableau give enterprise data and BI teams tools to visualize their company data and connect disparate data sources. These tools offer businesses analytics, visualization, and software integrations to better study their data and apply it to their operations. To decide which BI solution is better suited to your enterprise, consider the main tools your business needs, your analysts’ BI experience, and your most prioritized software integrations.
What is Looker?
Looker’s data modeling tools allow teams to link Looker to a database and use Structured Query Language (SQL) to define a data model. Looker provides pre-built modeling patterns so teams can immediately begin modeling without needing to write all of their own models. Looker also provides pre-built templates for quickly building dashboards from commonly accessed data sources like Google.
For developers, Looker offers an API for customizing workflows or developing enterprise-specific applications. Dev teams also have the option to build Looker extensions to share with Looker users outside their organization. Businesses that want to solve BI questions with other organizations will benefit from Looker’s collaborative development features.
What is Tableau?
Tableau is a data visualization and analytics solution owned by CRM provider Salesforce. Tableau connects to a wide variety of data sources, from databases to Google Workspace applications. It also offers analytics for Salesforce customers, analyzing data from the CRM alongside data from other business applications.
Tableau offers drag-and-drop functionality for creating data visualizations and allows inexperienced users to immediately begin designing dashboards. Tableau supports enormous warehouse workloads and large unstructured datasets for enterprises that need to analyze large stored volumes or data from high-performance applications.
What are the differences between Looker and Tableau?
Looker and Tableau differ in data modeling technology, integrations, and ease of use. Consider your business’s specific needs when evaluating each of these BI tools.
Looker vs. Tableau: Data visualization and modeling
For data modeling, Looker uses LookML, a coding system similar to SQL. When Looker is connected to an SQL database, users are able to automatically generate a LookML data model.
Looker offers over 100 prebuilt modeling patterns to help teams build their models. These patterns allow them to customize models based on enterprise-specific data measurement needs. Looker also develops a basic model for businesses by observing relationships between the tables in the organization’s data schema.
Looker offers visualization tools like dynamic dashboard filtering, which allows users to filter for individuals and groups, and an entire marketplace of visualization types, including maps, funnels, and timelines. Some customers felt that Looker’s visualization tools were weaker, though, and would have preferred the ability to customize them further.
Tableau offers visualization features like drag-and-drop, which allows data analysts to easily select dimensions like customer ID or postal code to view sales data. Analysts can also use natural language queries to view a graph of answers. Note that Tableau has no built-in template for a data dictionary, so creating visualizations from many different data sources may require manual work.
Tableau doesn’t provide strong data modeling features. If your data team needs to create models as well as visualizations, Tableau won’t provide sufficient tools to do so.
Bottom line: Consider Looker if your data teams need to easily build data modeling. If you need easy-to-learn visualization capabilities, especially for newer teams, consider Tableau.
Looker vs. Tableau: Integrations
Important Looker integrations include Salesforce and Slack. Looker allows teams to send data directly to Slack channels and use slash commands to search data within Slack. Looker is a useful solution for teams that heavily communicate via Slack and want to share LookML dashboards in those conversations.
Looker also integrates with Snowflake, among other SQL databases and data sources. For data teams experienced in SQL, Looker provides the tools to create an infrastructure of databases with a central source of data insights. Consider Looker if your BI professionals need database-intensive data analytics and integrations or want to use Snowflake alongside Looker.
Tableau offers API connections and native integrations with many other tools, including Splunk, Amazon Athena, and SAP HANA. It works with SQL databases and can retrieve data from tools like Shopify, Zendesk, and Snowflake. Tableau also has extensions for languages like Python and programs like MATLAB. If your team has data scientists or engineers that want to link their data models with their most commonly used programs or languages, consider Tableau.
Salesforce acquired Tableau in 2019, and customers that use both benefit from being able to analyze Salesforce data in Tableau. If your enterprise has an established Salesforce platform, your sales, marketing, and operations teams may also benefit from a partnership with the business intelligence team to better understand CRM data and customer behavior.
Bottom line: Tableau is beneficial for businesses that use Salesforce or store data in many applications. Looker is useful for businesses that want to compile data from many databases and is especially helpful for SQL-experienced teams.
Learn more about APIs and connecting applications: What is API Integration?
Looker vs. Tableau: Ease of use
Looker works on Mac, Windows, and Linux systems; it’s a good choice for data teams that use a variety of devices and operating systems. It’s highly customizable, which gives BI professionals flexibility in designing models. However, its customizability may mean a learning curve, especially for inexperienced team members.
Looker also receives highly complimentary user reviews for its customer support team. Consider Looker if your data team needs additional support from a BI vendor when implementing or using the solution.
Tableau is a tool for new or small data teams that need to start creating visualizations and dashboards immediately. It’s relatively easy to learn. Aside from desktop and laptop computers, Tableau works on both iOS and Android devices.
It has its own query language, VizQL, which allows teams to create visualizations based on the results from a query. VizQL supports SQL analytics capabilities while also letting data teams create temporary variables that don’t actually change the source data.
Keep in mind that Tableau’s many features can be overwhelming for inexperienced BI professionals. For advanced data operations like modeling, Tableau doesn’t provide native features or templates.
Bottom line: Tableau makes it easy to start creating visualizations, but exploring its other features takes time, as does the manual work required to compensate for its lack of modeling functionality. Although Looker’s high customizability might require heavy learning in the first few weeks or months, its customer support is a plus for teams that need extra help.
Looker vs. Tableau: Pricing
Looker pricing is available by requesting a quote from Google Cloud, its parent platform. Looker has multiple business plans, and generally speaking, its pricing is more affordable for larger data teams that have multiple users.
A single Tableau creator license costs $70/month, and the price is multiplied for each additional analyst on the plan. Viewer licenses, designed for executives, cost $15/user/month and allow leaders to view dashboards and visualizations created by the analytics team. Tableau’s pricing is suitable for both SMBs and larger companies.
Bottom line: Tableau has the edge on pricing for small businesses. Looker’s customizable pricing plans allow enterprises to design a solution with the features and capacity they need.
Is Looker or Tableau better for your business?
Looker is a good choice for teams experienced in SQL and organizations with multiple SQL databases. It can be used alongside other data analytics tools like Snowflake.
Large data teams that need the ability to develop models will benefit from Looker’s modeling tools. Looker is also a good solution for BI teams that have development experience and want to create their own apps or embed Looker analytics within existing company software.
Small and inexperienced teams will benefit from the ability to immediately create visualizations in Tableau. Enterprises with many data sources, including multiple databases, also benefit from Tableau’s integration options.
Consider Tableau if your enterprise or small business uses a variety of data sources or multiple non-Microsoft applications. Because Tableau supports so many data connectors, it’s a good choice for teams with scattered applications that need to pull all their information into one location for analytics.
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