The Power BI service is the cloud hub for sharing and automation, while Power BI Desktop is the Windows app for shaping data and building reports.
If you’re new to Microsoft’s analytics stack, two names pop up right away: the online service and the Desktop app. They sit on the same team but play different positions. One lives in the cloud where people view, refresh, and share. The other runs on your PC where you connect, clean, model, and design. Work starts local, then moves online for reach and governance. This guide shows where each fits, what they do best, and how to move work between them without friction.
Power BI Desktop: Build, Model, And Design Locally
Power BI Desktop is a free Windows application. You install it, point it at data, and craft interactive pages that answer real questions. Think of Desktop as your studio. You pull data from files, databases, and SaaS sources, reshape it with Power Query, build a model with relationships and DAX, then lay out visuals. When a page feels right, you publish to the online service so teammates can use it.
Core Things You Do In The Desktop App
- Connect and shape data: Use Power Query steps to clean, split, merge, and standardize before data hits the model.
- Model for fast, repeatable insight: Create relationships, measures, and calculated columns with DAX for reusable logic.
- Design polished report pages: Add visuals, bookmarks, slicers, and drill-through. Test with sample interactions before you share.
- Optimize: Trim columns, hide helpers, and check performance so pages render smoothly later in the browser.
When Desktop Is The Better Starting Point
Start in Desktop when the raw data needs shaping, when you’re modeling facts and dimensions, or when you’re composing multi-page, interactive stories. It’s also the right place for DAX-heavy logic, custom visuals testing, and detailed performance tuning on large models.
Power BI Service: Share, Refresh, And Govern In The Cloud
The service runs in the browser. After you publish from Desktop, you get workspaces, apps, dashboards, scheduled refresh, dataflows, and row-level security enforcement at scale. Viewers open reports anywhere, on desktop or mobile, without installing the authoring tool. Admins set roles, audit usage, and wire up gateways for safe refresh against on-prem sources.
Core Things You Do In The Online Service
- Distribute: Publish to a workspace, promote to an app, and share with groups so the right people see the right content.
- Automate refresh: Set schedules for imported models; keep DirectQuery and live connections flowing.
- Build dashboards: Pin tiles from reports, add KPIs, and set data-driven alerts that ping people when values cross thresholds.
- Secure and govern: Assign workspace roles, apply row-level rules, and manage lineage and impact analysis.
Power BI Service Vs Power BI Desktop: What Each One Does
Both pieces are part of one pipeline: author in Desktop, run and scale in the service. The app focuses on shaping and modeling. The browser side focuses on sharing, refresh, consumption, and control. That handoff is the magic: one click sends a report and its model to the cloud, where people can view it with a link.
Publishing Flow: From PC To Browser
- Build pages and measures in the Desktop file.
- Click Publish, pick a workspace, and send it to the cloud.
- Open the workspace in the browser to set audience access, refresh, and dashboards.
- Share the app link, or add the report to Teams, SharePoint, or PowerPoint.
Licensing Basics In Plain Words
Anyone can author with the Desktop app. For sharing in the service, people usually need a paid user license. Viewers without paid seats can still see content if it lives in a Premium capacity and they have access. Your admin chooses the mix: paid per user, Premium per user, or capacity-based plans in Fabric. The idea is simple: authoring is free; sharing and governance live behind licenses or capacity.
Data Refresh: Keep Reports Current
Imported models refresh on a schedule in the service. If your data source sits behind a firewall, install a gateway on a server in your network so the cloud can reach it safely. For direct connections to cloud databases, you can use DirectQuery or live connections with no scheduled import at all. Pick the mode that fits the source, load, and latency you need.
Gateways In A Nutshell
A gateway is a small Windows service that runs on-prem. It opens outbound traffic to Azure, so the service can send queries to your local SQL Server, Oracle, or file shares without opening inbound holes. You add data sources to the gateway, map them to your datasets, and your refresh jobs run on time.
Authoring Depth: Why Desktop Still Matters
Desktop gives you the canvas and the model in one place. It blends Power Query and DAX so you can shape, calculate, and design with tight feedback. You can keep a versioned file in Git, review changes, and control releases. When a measure needs a rewrite or a model needs a new table, you do that work locally where testing is quick.
Design Habits That Pay Off
- Stage clean data: Do merges, splits, and type fixes in Power Query, not in visuals.
- Model with intent: Keep star schemas, avoid many-to-many unless needed, and hide helper columns from the report view.
- Measure once, reuse: Write base measures, then layer time intel or filters on top instead of repeating logic.
- Trim the model: Drop unused columns and tables to keep memory lean and page loads snappy.
Collaboration And Distribution: Why The Service Shines
In the browser, you package reports into apps for clean rollout. You can stage changes in a workspace, test with a few people, then push to a wider group. Lineage views help you spot which datasets feed which reports, and usage metrics show who’s actually opening them. Alerts and subscriptions nudge busy teams at the right moment. The result is steady, safe delivery without emailing files around.
Security Choices That Keep Data Safe
- Workspace roles: Give build, edit, or view rights based on job duties.
- Row-level rules: Filter rows by user so each person sees only what they should.
- Data protection labels: Tag sensitive content and track activity with audit logs.
Picking The Right Tool For Each Task
Use the Desktop app when you’re shaping data, modeling, and designing pages. Use the service when you’re rolling out content, setting refresh, managing security, and driving adoption. Most teams jump between both in a single day: tweak a measure locally, publish, then check the app audience and refresh status online.
Common Scenarios And The Best Home
- New report from messy CSVs: Start in Desktop to clean and model, then publish.
- Daily KPI board for sales: Build once in Desktop, surface in the service as a dashboard with alerts.
- Strict data access rules: Author RLS in the model, enforce sharing from the service with groups and roles.
- Mixed sources on-prem and cloud: Use a gateway for local systems; let cloud sources connect directly.
Hands-On: A Fast Build-And-Share Loop
Step 1: Shape The Data In Desktop
Connect to a source, clean columns, create relationships, then add a few core measures. Keep names plain and readable. Add slicers and bookmarks for common paths people follow. Test with fake selections to spot logic gaps early.
Step 2: Publish To A Workspace
Pick a staging workspace for edits. After the push, open the report in the browser, try the filters, and check refresh. If the dataset imports from an on-prem source, map it to a gateway and set a schedule that lines up with business hours.
Step 3: Package As An App And Share
Create an app for a clean viewer experience. Add a short description, set a friendly landing page, and limit the audience to the right group. Send the app link in Teams or email. Add a subscription for a weekly snapshot to keep attention on the metrics that matter.
Feature Snapshot: Where Each One Fits
| Capability | Desktop | Service |
|---|---|---|
| Connect & shape data | Power Query steps on your PC | Dataflows for shared prep in cloud |
| Modeling & DAX | Full authoring and testing | Use the published model |
| Report design | Canvas, themes, bookmarks | Minor edits, interactions, view |
| Sharing & apps | Not for distribution | Workspaces, apps, share links |
| Refresh | Manual while authoring | Schedules, DirectQuery, live |
| Security | Define RLS rules in model | Assign roles, manage access |
| On-prem data | Design and test | Gateway bridges to sources |
| Usage insights | Local testing only | Usage metrics and lineage |
Tips For Smooth Team Adoption
- Use a staging workspace: Keep draft changes away from viewers until sign-off.
- Set refresh early: Wire a gateway or DirectQuery on day one, not launch day.
- Name like a human: Measures and pages should read like plain English.
- Ship an app, not links: One app beats a pile of report URLs.
- Watch usage: Drop or improve pages that nobody opens.
FAQ-Style Clarifications Without The FAQ Block
Do You Need The Desktop App If You Use The Service?
Yes for full authoring. The service can do light edits and dashboards, but deep data shaping and modeling belong in Desktop.
Can Viewers Use Reports Without A Paid Seat?
Yes, if content lives in a Premium capacity and the viewer has access. In all-per-user setups, both the publisher and the viewer need paid seats.
What About Security For Mixed Data?
Keep sensitive data on-prem, connect through a gateway, apply row filters in the model, and grant access in the workspace. That combo keeps data safe while still enabling cloud use.
Wrap-Up: A Simple Way To Decide
Build and model in the Desktop app. Share and run in the service. That split keeps authors fast and keeps distribution clean. Set up a gateway when data sits on-prem. Add refresh, roles, and an app. You now have a pipeline that turns raw sources into trusted pages people can open anywhere.
Learn the basics of the browser side with the Power BI service guide, and get the Desktop app details in the Power BI Desktop getting started page.