Overview

Power BI

Stacks991

Followers946

Votes29

Poli

Stacks356

Followers11

Votes0

GitHub Stars2.0K

Forks337

Poli vs Power BI: What are the differences?

# Key Differences between Poli and Power BI

Poli and Power BI are both powerful tools for data analysis and visualization, but they have key differences that set them apart.

1. **Data Sources**: One key difference between Poli and Power BI is the range of data sources they support. Poli primarily focuses on connecting to cloud services like Google Analytics, Salesforce, and MySQL databases. In contrast, Power BI offers a wider variety of connections, including on-premises data sources and popular cloud services like Azure, AWS, and Google Cloud Platform.

2. **User Interface**: Another difference lies in the user interface of Poli and Power BI. Poli is known for its simple, user-friendly interface that makes it easy for beginners to create basic visualizations. On the other hand, Power BI provides a more robust interface with advanced features and customization options, making it suitable for users with more complex data analysis needs.

3. **Collaboration and Sharing**: Power BI shines when it comes to collaboration and sharing capabilities. With Power BI, users can easily collaborate on reports and dashboards in real-time, share insights with stakeholders, and publish reports to the web or embed them in other applications. Poli, on the other hand, lacks the same level of collaboration features, making it less suitable for team-based projects.

4. **Pricing**: Pricing is another significant difference between Poli and Power BI. Poli offers a free plan with limited features, while Power BI also has a free version but with more robust functionality. Power BI's paid plans, however, can be more cost-effective for larger organizations that require advanced analytics capabilities and extensive data storage.

5. **Advanced Analytics**: Power BI has a clear advantage when it comes to advanced analytics features. Power BI offers a wide range of AI-powered capabilities such as automated machine learning, natural language querying, and predictive analytics, allowing users to gain deeper insights from their data. Poli, while a capable tool for basic visualizations, lacks the same level of advanced analytics functionality.

6. **Integration with Microsoft Ecosystem**: As a product developed by Microsoft, Power BI seamlessly integrates with other Microsoft tools and services such as Excel, SharePoint, and Dynamics 365. This integration provides a seamless experience for users who are already using Microsoft products, offering a cohesive ecosystem for data analysis and reporting. Poli, while compatible with various platforms, does not have the same level of integration with the Microsoft ecosystem.

In Summary, Poli and Power BI differ in terms of data sources, user interface, collaboration features, pricing, advanced analytics capabilities, and integration with the Microsoft ecosystem, making each tool suited for different user needs and preferences.

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Advice on Power BI, Poli

Vojtech

Head of Data at Mews

Nov 24, 2019

Decided

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

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Detailed Comparison

Power BI	Poli
It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards.	It is an easy-to-use BI server built for SQL lovers. Power data analysis in SQL and gain faster business insights. It is a platform independent web application.
Get self-service analytics at enterprise scale; Use smart tools for strong results; Help protect your analytics data	Self-hosted & easy setup; Connect to any database supporting JDBC drivers; SQL editor & schema viewer
Statistics
GitHub Stars -	GitHub Stars 2.0K
GitHub Forks -	GitHub Forks 337
Stacks 991	Stacks 356
Followers 946	Followers 11
Votes 29	Votes 0
Pros & Cons
Pros 18 Cross-filtering 4 Database visualisation 2 Powerful Calculation Engine 2 Intuitive and complete internal ETL 2 Access from anywhere	No community feedback yet
Integrations
Microsoft Excel	Oracle PostgreSQL Elasticsearch Windows

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