Looker customers have the option to deploy their platform instance in the environment that best suits their unique needs. Many customers choose to deploy Looker on flexible and convenient public cloud services while others opt to host on-premises.
Either way, customers experience the Looker platform exactly the same. They have complete control to seamlessly migrate from one environment to another over time without disrupting users and dependent business processes. Seamless migration across cloud databases within these environments is made possible by LookML, Looker’s unique modeling layer, which decouples centrally defined business logic from the underlying data.
The Power BI service is a cloud offering, but can only be deployed in Microsoft’s own Azure public cloud environment (and is optimized for underlying Azure databases). This limitation introduces a significant barrier to IT organizations that may want to leverage the services of a different public cloud provider offering more favorable pricing, better features, or better support for a particular region of the world.
An on-prem version called Power BI Report Server is available, but the feature differences between it and the Power BI Azure service are significant and introduce confusion and complexity for end-users. Power BI is based on a collection of disjointed in-memory cubes stored in Azure, rather than a centrally defined metadata layer, which makes migration across underlying cloud databases extremely challenging to end-users.
Customers tell us that flexibility and adaptability are key when it comes to choosing a solution that can deliver value today and well into the future. Looker customers who compared our solution against Power BI most frequently cite the following advantages of the Looker Platform:
Looker’s architecture was designed from the ground up to leverage the native scalability and performance of modern cloud databases and allows you to choose the cloud provider best suited to your needs. More importantly, Looker’s multi-cloud capability makes your data strategy future-proof. You can easily change where you choose to deploy Looker and which underlying cloud database(s) you use with no downstream impact to your end-users.
Power BI customers are constrained to deploying in Microsoft Azure, restricting their ability to take advantage of the services available in other public cloud environments. While this limitation may not seem like an immediate issue for organizations using Microsoft and Azure services exclusively, it does introduce complexities in the future if other cloud environments are more appealing or are more price competitive.
The dependency built on Power BI as an exclusive Azure service creates high switching costs, which significantly limits customer choice and the ability to take advantage of the breadth and depth of cloud offerings beyond what is available in Azure.
Looker leverages a powerful SQL-based modeling language called LookML. LookML enables advanced business analysts already familiar with SQL to contribute to a git version-controlled data model where all business rules and definitions are centrally defined and managed. Because LookML shares so many similarities with SQL, business analysts are typically able to start data models in Looker with a very short learning curve. Looker doesn’t store any data or pre-aggregate into data cubes either, so analysts can quickly adapt LookML models to meet the needs of their business.
On the contrary, Power BI users doing anything more than consuming existing dashboards will need to learn a complex language called DAX (Data Analysis Expressions), designed to query multidimensional data stored in tabular in-memory models. Extensive training and technical expertise are required in order to use DAX, and the learning curve can be extremely long because neither is based on skills that analysts already have (DAX is similar to MDX, which is used to query older SQL Server Analysis Services cubes).
Looker customers experience a 100% browser-based experience without the need to install and maintain desktop client software for their users. More importantly, the user experience is identical regardless of Looker deployment location. Customers who subscribe to the Looker-hosted offering have the exact same experience as those who choose to self-administer and host in their preferred public cloud environment or on-prem.
The Looker experience is contained to a single platform that provides a seamless and intuitive experience for data engineers, content curators, and line of business consumers to execute their respective analytic workflows.
While the core Power BI offering is a cloud-based Azure service, there is a desktop component that is required to author and publish content to the Power BI service in order to share it and make it available for consumption.
Power BI can also be deployed on-prem via the Power BI Report Server, but the available features and end-user experience are not at parity with what is available via the Azure-based Power BI service. This disconnect, coupled with a desktop dependency, can often create unnecessary overhead for administrators as well as complexity and confusion for content authors and consumers.
The foundation of Looker’s platform is its centrally managed modeling layer, which ensures consistency in defining all dimensions and measures because they are defined once and maintained centrally. This modeling layer guarantees that all curated content (reports, dashboards, etc.) renders accurate, timely, and consistent metrics. It also gives non-technical users the ability to freely explore the data model to ask and answer their own questions in an intuitive interface.
In fact, Looker customers often create some of their most business-critical dashboards as the result of a data exploration exercise where the process of asking and answering questions surfaced new KPIs and indicators worthy of tracking on a production dashboard.
The concept of exploration as a means of developing content in Power BI is nascent as it was designed to enable authors to build charts and dashboards based on requirements provided by the business.
Rather than using exploration to discover their own insights, Power BI business users need to provide dashboard specifications and requirements to more technical users who have the skills needed to connect to the underlying data and develop and deploy the dashboard. Once built, users can self-serve — but only within the parameters of what has been made available to them (and until they come up with a question that their dashboard can’t answer).
Looker is so different from Power BI and other competitors when it comes to support that we have our own name for it. We call it DCL, the Department of Customer Love.
Looker prioritizes customer feedback and relationships above all else. Instead of placing them in a technical support queue where they're forced to wait days for a response, we connect customers with a person who cares about solving their issue.
Looker customers can have an in-product, live chat with a DCL support engineer any time they need help with a particular feature, or have a question about the product — without leaving the platform.
Customers consistently rate Looker support as one of the most appreciated features of our product.
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