Microsoft Power BI

Frequently Asked Questions about Power BI 

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Microsoft Power BI is a powerful business intelligence solution that helps organizations transform data into understandable insights. With this tool, you can collect, analyze, and visualize data from various sources in interactive dashboards and reports.

This FAQ section answers the most common questions about Power BI, from basic functionalities and licensing options to advanced usage possibilities and performance optimization. Whether you're a beginner or looking to deepen your Power BI skills, these answers provide the practical information you need to work successfully with this versatile data visualization platform.

What is Power BI?

Power BI is de business analytics-dienst van Microsoft die interactieve visualisaties, business intelligence-mogelijkheden en rapportagetools biedt. Gebruikers kunnen dashboards, rapportages en apps maken die inzichten verschaffen uit verschillende gegevensbronnen, waardoor organisaties data-gestuurde beslissingen kunnen nemen. Power BI is beschikbaar als desktopapplicatie, als SaaS-dienst (Software as a Service) en als mobiele app. 

Is Power BI free to use?

Power BI offers multiple licensing options. Power BI Desktop is free to download and use for creating reports and visualizations. Power BI Service has a free version with limited features and storage capacity. For advanced features, sharing capabilities, and larger data volumes, organizations typically use Power BI Pro or Power BI Premium, which provides dedicated capacity and additional features for larger enterprises

Which data sources does Power BI support?

Power BI can connect to hundreds of data sources, including:

  • Excel, CSV and SharePoint

  • SQL Server, Azure SQL Database

  • Cloud services like Salesforce and Google Analytics

  • Microsoft Dynamics 365

  • Big data-solutions like Hadoop and Spark

  • Web-API’s and custom connectors

This makes Power BI a versatile data visualization platform for diverse sectors.

What is DAX in Power BI?

DAX (Data Analysis Expressions) is a formula language used in Power BI for creating custom calculations and data manipulations. DAX resembles Excel formulas but is more powerful and enables users to create calculated columns, measures, and tables. This enables complex data analysis and the creation of key performance indicators (KPIs) that can be visualized in reports and dashboards.

How often can Power BI refresh data? 

Depending on your licence Power BI offers:

  • With Power BI Pro or Premium Per User, you can schedule up to 8 refreshes per day

  • Power BI Premium capacity allows up to 48 refreshes per day

  • The free Power BI service limits scheduled refreshes to once per day For real-time data analysis, Power BI also offers Direct Query and real-time streaming dataset options.

Can Power BI process large datasets? 

Yes, but with some caveats. Power BI Desktop can process millions of rows, depending on your computer's specifications. However, the free Power BI Service has a limit of 1GB per dataset. Power BI Pro increases this to 10GB per dataset. For truly large datasets (up to 400GB), organizations should consider Power BI Premium, which provides dedicated capacity and significantly higher performance for large-scale business intelligence implementations.

How can I share Power BI reports?

Depending on your Power BI-licence:

  • Power BI Free: You can export reports as PDF or PowerPoint presentations 

  • Power BI Pro: You can share reports directly with other Pro users, create app workspaces and publish to the Power BI service 

  • Power BI Premium: You can share content with users who do not have a Pro-license via Power BI apps 

What skills do I need for Power BI?

To become proficient in Power BI, you need to develop the following skills:

  • Data modeling concepts (relationships, star schemas) 

  • DAX formula language for calculations 

  • Power Query for data transformation 

  • Best practices for visualisations 

  • Basic knowledge of databases and data structures 

  • Knowledge of the data sources and business requirements of your organisation 

Is Power BI safe for sensitive company data?

Yes, Power BI contains robust security features, including:

  • Row-level security (RLS) to restrict data access based on user roles

  • Integration with Azure Active Directory for identity management

  • End-to-end encryption for data in transit and at rest

  • Data loss prevention capabilities

  • Compliance with major standards and regulations, including GDPR, HIPAA, ISO 27001, and SOC2 

Organisations can implement additional security measures through careful rights management and governance policies.

What are the limitations of Power BI?

Although Power BI is powerful, it has some limitations: 

  • Complex data transformations can impact performance

  • Specific visualizations may require custom development

  • The free version has significant limitations for sharing and collaboration

  • Some advanced features require Premium licenses

  • Report customization has some limitations compared to traditional reporting tools

  • Large datasets may require careful optimization for good performance

Many of these limitations can be addressed through good architecture, the right licensing choices, and development practices.

What is the difference between Power BI Desktop and Power BI Service?

Power BI Desktop is a Windows application used for creating reports and data models. It provides tools for connecting to data sources, transforming data, creating relationships, and designing visualizations.

Power BI Service is the cloud-based platform where you publish, share, and collaborate on reports. It adds features like dashboards, apps, scheduled data refresh, and collaboration capabilities.

Most Power BI use cases involve developing reports in Desktop and then publishing them to the Service for distribution and use.

How can I improve the performance of my Power BI report?

To optimize the performance of Power BI: 

  • Use efficient data models with appropriate relationships

  • Limit the number of visualizations per page

  • Apply filters early in the data pipeline

  • Use calculated columns sparingly; use measures instead

  • Implement query folding where possible

  • Consider Direct Query mode for very large datasets

  • Remove unnecessary columns and rows during data import

  • Use aggregations and incremental refresh for large tables

  • Avoid complex DAX calculations that cannot be optimized

Regular testing using Performance Analyzer can help identify specific bottle necks in your reports. 

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LOCATIONS

Basisweg 32

1034 AP

Amsterdam

Rithmeesterpark 50-A1

4838 GZ Breda

© AppReef B.V. Created with systeme.io