Looker Studio vs Power BI for Owner Weekly Reports

The short verdict

Pick the tool that sits closest to your data. If most of the figures your owner wants come from Google Analytics, Google Ads, Search Console, Google Sheets or BigQuery, Looker Studio is usually the cheaper and quicker route. If the figures come from Excel files on SharePoint, a Microsoft-based finance system or Dynamics, Power BI usually fits better. Neither tool is a good answer for a business whose data lives in five unrelated systems with no clean export. In that case the cost is in the data work, not the dashboard.

Comparison at a glance

The table below lists what each product publishes today. Where a vendor does not publish a figure, the cell says so. Prices are US list prices in US dollars. Final prices can differ by country and by contract, so check the vendor's own pricing page before you buy.

Who each tool suits

Looker Studio suits an owner or operations lead who wants a weekly page of figures from Google sources, emailed on a schedule, and who does not want to pay for every reader. A marketing-led business with Google Ads and Analytics is the classic fit. A service firm that keeps its bookings in Google Sheets can also use it without new licences.

Power BI suits a business that already runs on Microsoft 365 and keeps its finance figures in Excel or a Microsoft-linked system. It fits well when a finance or operations person will build and maintain the model, and when the owner needs filters, drill-down and a more formal data model. A business in Lagos that reports from Excel files on SharePoint and a distributor in Manchester using Dynamics would both find Power BI a natural match. A bakery in Singapore that tracks orders in Google Sheets and ads in Google Ads would find Looker Studio more natural.

Neither tool is worth the effort for a business with one or two readers, a single spreadsheet and a weekly report that takes ten minutes to type. A plain email with a table may do the job better.

Total cost beyond the licence

The licence is the smallest line in most budgets. Four other costs usually decide the real figure.

Setup is the first. Each data source needs a connection, a check of field names, and a test against a known total. Partner connectors for non-Google systems are often paid, and their prices are set by each connector maker. Look at their own pricing pages before you commit.

Maintenance is the second. Reports break when a column is renamed in a spreadsheet, when a tax field changes, or when an ad platform changes its API. Someone must check the numbers every week, not only when something looks odd.

Breakage is the third. Looker Studio reports that draw on a shared Google Sheet fail when the sheet owner leaves or changes permissions. Power BI models can fail on refresh if a gateway or credential expires. Assign a named owner for each source and write down who can reset each login.

Vendor lock-in is the fourth. Power BI sharing depends on the Microsoft licence model. Content in Premium Per User workspaces can be viewed only by other Premium Per User users, so moving a report to a cheaper tier later can mean rebuilding access. Looker Studio reports can be shared with any Google account holder, but they still depend on Google data sources. Ask who will own the report files and where the source credentials are stored before you start.

When a custom-built report wins

A custom report, built by a developer or an automation consultancy, wins when the owner needs figures from three or more systems with different owners, or when the calculation rules are unusual. A common example is a weekly view that combines bank feeds, invoices and a payroll export, then applies internal approval steps. In those cases a dashboard tool is still a display layer. The hard work is the joining, checking and rule-setting that sits behind it.

A custom build also brings its own risks. Someone must maintain the code or workflow, document it, and test it after each software change. If that person leaves, the report can stop working. It is also harder to hand over than a standard tool that many staff already know. Choose a custom build only when the saving from automation is clear after the setup and upkeep costs are counted.

Migration notes

If you move from Looker Studio to Power BI, or the other way, start with a list of every data source, every reader and every scheduled delivery. Rebuilding the visuals is usually the easy part. Checking that totals match the old report for at least four weeks in a row is the step most teams skip.

Watch for the name change. Google renamed Looker Studio back to Data Studio on 11 April 2026, and the product went live under the new name on 16 April 2026. Existing reports moved over automatically, according to Google's announcement. Check your own report links after the change, and keep a note of the account that owns each report.

Avoid moving a Power BI tenant between regions as a quick fix. Microsoft's guidance says a tenant remap deletes the old tenant and recreates it, that capacities must be reprovisioned, and that some usage data is lost. Plan that step with your Microsoft administrator, not as part of a weekly report project.

Personal data in reports is a separate question. Check your local data protection law before you share customer names or payroll figures with a wider group of readers, and limit access to what each reader needs.

What automation cannot do here

A dashboard tool shows the figures it receives. It cannot tell you that a supplier invoice was entered twice, that a sales team left a deal out of the CRM, or that an ad account was paused by mistake. A person still needs to check the totals, agree the definitions and decide what the owner should read first. Results depend on your own figures and on how clean your source data is. The free audit measures that before any tool is chosen.