Power BI vs Tableau vs Looker: A 2026 Comparison

Power BI, Tableau and Looker are three names that come up again and again when an organisation chooses a business intelligence platform, and when a new analyst decides which tool to learn. All three connect to data, build interactive dashboards and share them securely. The differences lie in how each one models data, where reports are built, and which kind of team it assumes. This comparison is based on each vendor's own documentation rather than on rankings, and it avoids prices, which change often and vary by agreement.

At a glance

Power BI: Microsoft's integrated option

Power BI has two main parts: Power BI Desktop, a Windows app used for data modelling and report creation, and the Power BI service, used for sharing and collaboration. Desktop uses Power Query for transforming data and DAX for calculations, and Power BI is now a core part of Microsoft Fabric (Microsoft Learn: what is Power BI). Desktop is a free download, while sharing through the service is organised by plans such as Pro, Premium Per User and Fabric capacity (Microsoft: Power BI pricing).

Each table in a Power BI model has a storage mode. Import stores a snapshot of the data for fast visuals and needs a refresh to show new data; DirectQuery sends queries to the source when visuals load, translating DAX into the source's language, such as SQL (Microsoft Learn: storage mode). Import is available for almost all data sources and gives the fastest visuals; DirectQuery suits data that is too large to import or must always be current, at the cost of slower queries.

Choose Power BI when the organisation already works in Microsoft 365, Excel and Azure, when report authors are Excel users, and when one platform for preparation, modelling and sharing matters. The main practical limitation is that Desktop runs on Windows only. Excel vs Power BI covers the move from spreadsheets, and star schema data modelling in Power BI the model design that makes DAX simpler.

Tableau: built around visual exploration

Tableau's strength is exploring data visually: dragging fields onto rows, columns and marks to find patterns quickly. Tableau Desktop is available for both Windows and Mac (Tableau Help: install Tableau Desktop). Data can be queried through a live connection or through an extract, a separately saved subset of the data used for performance and for features the original source does not support (Tableau Help: extracts).

For calculations, level of detail expressions let authors compute values at a different granularity from the view, with INCLUDE, EXCLUDE and FIXED (Tableau Help: LOD expressions). Teams share work by publishing to Tableau Server or Tableau Cloud; individuals can use Tableau Public, a free cloud service, but everything published there is publicly visible (Tableau Help: publishing), so it suits portfolios and open data, never company data.

Choose Tableau when exploratory, highly visual analysis is the main job, when authors use Macs, or when the organisation already has Tableau Server or Cloud.

Looker: a governed semantic layer

Looker takes a different approach. Instead of each author building a model in a desktop file, a data team defines the business logic once in LookML, Looker's modelling language. Looker then uses the model to generate SQL against the database, so business users can explore without writing SQL, and LookML projects are typically version-controlled together in a Git repository (Looker: what is LookML).

The result is consistency: "revenue" means the same thing in every report because it is defined in one place, reviewed like code. The price is that someone must build and maintain the model, which requires SQL and modelling skills, and the data must live in a database Looker can query, typically a cloud warehouse.

Choose Looker when a data team wants governed, reusable metric definitions on a cloud warehouse, and many business users need self-service exploration within those definitions.

Do not confuse Looker with Data Studio

Google's free dashboard tool, formerly called Looker Studio, is now called Data Studio (Google Cloud: Data Studio). It is a separate, lighter product for reports and dashboards, not the Looker platform described above. For small teams with data in Google Sheets or BigQuery, it is often the simplest starting point; the Data Studio tutorial builds a first dashboard.

How to choose for a team

1. Start from the existing stack. A Microsoft 365 organisation gets integration benefits from Power BI; a Google Cloud warehouse points towards Looker; existing Tableau Server licences and skills count too.
2. Decide who builds reports. Excel-skilled analysts adapt quickly to Power BI; visual explorers to Tableau; Looker needs a data team to own the model.
3. Decide how important governed definitions are. Many teams building reports independently risk inconsistent metrics, which Looker's central model or shared Power BI semantic models address.
4. Check authors' operating systems and the organisation's data residency and security requirements.
5. Run a pilot with your own data and a real report before committing, and include licence costs for everyone who will view reports.

Which should a learner choose?

Look at job listings where you want to work and learn what they ask for. The concepts transfer: SQL, data modelling with fact and dimension tables, defining metrics carefully, and designing clear dashboards, covered in dashboard design principles. An analyst who knows one tool well and understands these concepts picks up a second far faster than someone starting from scratch. Data analyst vs business analyst explains how the tool mix differs between those roles.

Power BI Desktop, Power Query, DAX and publishing to the Power BI service are covered in the Power BI course.

Sources

• What is Power BI? (Microsoft Learn) — Microsoft Learn
• Power BI pricing (Microsoft) — Microsoft
• Table storage mode in Power BI semantic models (Microsoft Learn) — Microsoft Learn
• Extract your data (Tableau Help) — Tableau
• Create level of detail expressions in Tableau (Tableau Help) — Tableau
• Publish data sources and workbooks (Tableau Help) — Tableau
• Download and install Tableau Desktop (Tableau Help) — Tableau
• What is LookML? (Looker documentation, Google Cloud) — Google Cloud
• Data Studio documentation (Google Cloud) — Google Cloud