Microsoft Power BI has established itself as a premier business intelligence solution, enabling organisations to convert raw data into meaningful reports and interactive dashboards. Enrolling in a Microsoft Power BI Course will give you the knowledge you need to grasp this powerful technology. However, before going into the learning process, it’s critical to grasp the major distinction between two critical Power BI components: Power BI Desktop and Power BI Service.
Table of Contents
- Understanding Power BI Desktop
- Understanding Power BI Service
- Key Differences Between Power BI Desktop and Power BI Service
- Functionality
- Deployment
- Data Refresh
- Sharing and Collaboration
- Conclusion
Understanding Power BI Desktop
Power BI Desktop is a sophisticated programme that can be used to build and develop data models, reports, and visualisations. It is a Windows-based programme that comprehensively collects data processing, modelling, and visualisation tools. Connect to numerous data sources, shape and clean the data, develop associations across tables, and create attractive visualisations using Power BI Desktop to acquire useful insights from your data.
Analysts, data professionals, and report developers utilise Power BI Desktop to construct and prototype data models and report locally on their PCs before publishing them to Power BI Service for wider dissemination.
Understanding Power BI Service
On the other hand, Power BI Service is a cloud-based platform for sharing, collaborating, and distributing Power BI material throughout your organisation. Power BI Service, Power BI Online or just Power BI allows you to securely publish your reports and dashboards to the cloud, making them available to colleagues, stakeholders, or anyone you want to share the insights with.
Power BI Service is accessed through a web browser. It offers collaboration capabilities, such as establishing workspaces, sharing material with certain individuals or groups, and setting up data-driven alerts. Furthermore, Power BI Service allows you to schedule data refreshes for your reports, ensuring that the data in your dashboards is always up to date.
Key Differences Between Power BI Desktop and Power BI Service
Here are the key differences between the Power BI desktop and Power BI service:
Functionality
Power BI Desktop primarily concerns data modelling, transformation, and report development. It has many options for altering data, constructing relationships, and producing sophisticated visualisations natively on your computer.
In contrast, Power BI Service emphasises cooperation and sharing. While Power BI Service allows you to see and interact with reports, the capacity to develop and alter reports is limited compared to Power BI Desktop.
Deployment
Power BI Desktop is a stand-alone programme that you install on your computer. Reports and models are created locally and then published to Power BI Service for sharing and collaboration.
Power BI Service is a cloud-based platform accessed using a web browser. It lets you view, share, and collaborate on reports and dashboards from any location with an internet connection.
Data Refresh
Power BI Desktop does not support data refresh. You may schedule data refreshes once you publish your reports to Power BI Service to guarantee that your reports’ data are always current.
Data refresh features are provided by Power BI Service, which allows you to arrange automated refreshes for your datasets at regular intervals.
Sharing and Collaboration
Power BI Desktop is not intended for direct report sharing with others. It is generally used for developing and prototyping reports before submitting them to Power BI Service for further distribution.
Conclusion
Power BI Desktop lets you create data models, reports, and visualisations locally on your computer. Conversely, Power BI Service is a cloud-based platform where you can communicate with stakeholders and share reports and dashboards. Enrolling in a Microsoft Power BI course can improve your understanding of these tools and help you become an expert in data analysis and visualisation, increasing your ability to use data-driven decision-making.
