In today's dynamic and data-centric business environment, your team's ability to extract actionable insights from your business intelligence tool is paramount to your success.
As organizations strive to stay competitive and agile in a rapidly evolving marketplace, the right BI tool can be a game-changer. Looker and Power BI are two major contenders in this domain. Both tools are known for their ability to provide insights, support decision-making processes, and streamline data analysis.
In the following sections, we will compare Looker vs Power BI and contrast these two solutions so you can make an informed choice about which BI tool is best for your business.
Looker, acquired by Google Cloud Platform in 2019, is a data exploration tool designed for reporting and dashboarding. It utilizes a proprietary modeling language called LookML, which allows users to define and manage data models in a structured manner. Looker emphasizes data quality and governance, offering a semantic layer built on LookML for managing metric definitions.
On the other hand, Power BI is Microsoft’s product business analytics platform. It was designed with a focus on power users who are more technically savvy. Positioned as an enterprise-level business intelligence platform, Power BI helps organizations access and present their data visually.
Although Looker and Power BI share the common goal of providing business intelligence, they each bring a distinct set of advantages to the table. Let’s take a closer look at the fundamental differences between Looker vs Power BI.
While comparing Looker vs Power BI in terms of data prep, Looker stands out with its code-first approach driven by LookML, providing precise control over the data quality and data governance of data models. Analysts like Looker because it supports version control, aiding collaboration among teams and ensuring transparency in changes made to data models. Google Cloud’s new solution, Duet AI, is built to help accelerate the speed of data modeling through natural language generation. However, the learning curve associated with LookML may pose challenges for users who aren’t familiar with the platform.
Power BI, with its familiar interface for Microsoft users, offers seamless integration with Microsoft data sources. Its data preparation tool, Power Query, may be more accessible to users with varying technical backgrounds. Leveraging its data profiling features, users can quickly understand the structure and quality of their data. Despite its user-friendly approach, challenges may arise in performance, particularly in handling large-scale data scenarios.
Looker’s dynamic dashboard filters offer users the ability to quickly find specific visualizations. The visualizations are tightly integrated with LookML, which provides users with a clear understanding of dimensions, attributes, and measures. However, its native visualization options offer limited ability for customization.
In contrast, Power BI boasts a wide range of chart types. While there is variety, they are notably simplistic. Neither Looker nor Power BI allow business users to limitlessly drill down into the data to answer their next question, which ends up creating more work for data teams.
When it comes to analytical comparison between Power BI vs Looker, Looker's strength lies in its enterprise-scale handling of data with LookML-driven data governance. Changes to the data model automatically extend to related reports, ensuring consistency across the organization. That said, the rigid governance layer may impact the speed and agility of companies operating in dynamic data environments.
Power BI’s DAX calculation language is tailored for users within the Microsoft ecosystem. Its focus on technical users allows for advanced analytics and data-science-centric use cases. Both Looker and Power BI cater to highly skilled data teams, which can pose challenges for business users. The emphasis on self-service analytics might be overshadowed by the initial learning curve.
Looker with its git-integrated version control system enhances collaboration for technical users by allowing multiple team members to work on the same LookML model simultaneously. The connection with Google Workspace tools, such as Slides and Sheets, enhances collaboration and data utilization.
While Power BI may lack the finesse of Looker's version control, it facilitates quick dashboard integration for Microsoft ecosystem applications like Salesforce and SharePoint. However, its Git integration is perceived as less intuitive compared to Looker.
The pricing structure for Looker consists of two primary elements: Platform pricing, which covers the expenses associated with operating a Looker instance, and user pricing, which involves licensing fees for individual users to access the Looker platform. The overall cost is dependent on the user type and the permissions granted within the Looker platform.
Power BI is accessible at no cost for Microsoft customers, to a point. If you require advanced features—such as increased sharing capabilities, expanded storage, or enhanced performance—you’ll need to license a premium version of the product.
In the era of rapidly advancing technology and data-driven decision-making, organizations are actively exploring business intelligence platforms that offer enhanced agility and user-friendliness. While Looker and Power BI are established players, there's a noticeable trend toward solutions that prioritize an intuitive user experience suitable for users of all proficiency levels.
ThoughtSpot's AI-Powered Analytics not only offers the baseline necessities, like a diverse range of data connection sources and analytics features, but also stands out for its emphasis on self-service analytics. ThoughtSpot Sage helps businesses securely utilize Gen AI on their data, enabling natural-language search, augmented analytics, and AI-assisted data modeling. Organizations leveraging ThoughtSpot are undergoing a transformative shift in how their teams interact with and extract value from their data.
Moreover, the ThoughtSpot Enterprise plan is built to handle large volumes of data with consumption-based pricing, so you only pay for what you need. We also offer an accessible Team Edition for only $95 per month.