In this post, we compare two popular BI tools: Microsoft Power BI and Amazon QuickSight. We’ll discuss the key differences between the two platforms and give recommendations, including their data source compatibility, data visualizations, collaborations, pricing, and advanced features.
Both tools offer powerful data visualization and analysis capabilities, so it ultimately comes down to which one better fits your needs and budget.
In this post, we’ll compare Microsoft Power BI and Amazon QuickSight to help you choose the right tool.
Power BI vs Amazon QuickSight: Overview Comparison
What Is Microsoft Power BI?
Microsoft Power BI is a business intelligence tool that helps you analyze and visualize your data in a user-friendly way. It lets you connect to different data sources, transform and clean the data, and create interactive dashboards, reports, and visualizations that you can share with others.
Image source: Microsoft Power BI
Real world examples of Power BI is for example, NBA team the Miami Heat use business intelligence to transform their customer interactions and business operations or the Carnegie Mellon University use Power BI to optimize energy and operational efficiency in buildings
What is Amazon QuickSight?
Amazon QuickSight offers a range of features to help you analyze your data, including data preparation, data analysis, and data visualization tools. With QuickSight, you can easily connect to various data sources, create dashboards and reports, and share insights with others.
Image source: Amazon QuickSight
Business Intelligence tools are types of software used to gather, process, analyze, and visualize large volumes of past, current, and future data in order to generate actionable business insights, create interactive reports, and simplify the decision-making processes.
1. Power BI vs Amazon QuickSight: Data Sources and Connectivity
Data integration is the process of combining data from multiple sources, often with the help of a data warehouse, into one unified view, which enables users to analyze the data holistically.
How does data integration work in Microsoft Power BI?
With Power BI, you can connect to various types of data sources, including Excel spreadsheets, cloud-based and on-premises data warehouses, and more.
Once the data sources are connected, you can create visualizations that display the data in an interactive and immersive way. These visuals can be sliced, filtered, highlighted, and drilled into to explore the data in more detail
Image source: Microsoft Documentation Power BI
Data Source Types
Power BI can connect to a wide range of data sources, including spreadsheets, databases, and cloud-based systems. With Power BI, you can access data from various sources such as
- Google Sheets
- And many more..
And cloud databases such as
- Microsoft Azure
- Amazon Web Services (AWS)
- Google Cloud
- Several others ..
Additionally, Power BI can connect to a variety of popular database management systems like MySQL, Oracle, and SQL Server, as well as Hadoop and NoSQL databases like Apache Cassandra and MongoDB.
Power BI also supports direct connectivity to cloud-based data sources such as Salesforce and Google Analytics, making it easy to analyze data from various sources in one place.
For a complete view on data sources, see the Microsoft documentation on Power BI data sources
How does data integration work in Amazon QuickSight?
Amazon QuickSight offers native connectivity to a range of data sources, including AWS services, databases, and third-party applications. You can easily connect to your data and start analyzing it in minutes.
In Amazon QuickSight, data integration works by allowing you to connect to multiple data sources, such as Amazon S3, Redshift, and RDS databases, as well as third-party data sources like Salesforce and Google Analytics.
Once the data sources are connected, users can perform data transformations, such as filtering, merging, and aggregating, to prepare the data for analysis. Amazon QuickSight also provides a range of data preparation features, such as data profiling, data cleaning, and data modeling, which help users to identify and address any data quality issues before performing analysis.
Below is an example of a workflow in Quicksight. Notice the first step, connect your data
Image source: Amazon QuickSight Documentation
Data Source Types
Amazon QuickSight can connect to many different types of data sources. This includes data sources such as databases (such as Amazon Redshift, MySQL, and PostgreSQL), cloud-based data sources (such as Amazon S3, Amazon Athena, and Salesforce), and even files (such as CSV, Excel, and JSON).
QuickSight also has built-in connectors for certain popular services like Google Analytics and AWS services like Amazon Aurora and Amazon RDS.
Summary: Data Sources for Microsoft Power BI vs Amazon QuickSight
|Data Source||Amazon QuickSight||Power BI|
|Alibaba Data Lake and Analytics||No||Yes|
Recommendation: AWS QuickSight vs Powre BI for Data Integration and Sources
Generally speaking, I would recommend Microsoft Power BI for data integration and sources. Power BI has a wide range of data connectors that make it easy to connect to various data sources, both cloud-based and on-premises.
In addition, Power BI has robust ETL (extract, transform, load) capabilities, allowing you to manipulate and transform data before loading it into your visualizations. Power BI also provides data modeling features that enable users to create complex data models and relationships.
These features make it easier to handle large volumes of data, reducing the time and effort required for data preparation.
Amazon QuickSight, on the other hand, has limited data connectors and is mostly geared towards cloud-based data sources. While it does provide ETL capabilities, they are not as robust as those of Power BI.
QuickSight’s data modeling capabilities are also limited compared to Power BI, which may be a challenge for more complex data integration scenarios.
Overall, from my experience, Microsoft Power BI is the better choice for data integration and sources due to its wide range of connectors, robust ETL capabilities, and powerful data modeling features.
2. Power BI vs Amazon QuickSight: Data Visualization and Reporting
Data visualization is the graphical representation of information and data.
Like dashboards, data visualization is synonymous with business intelligence. Data visualization is the practice of representing information graphically to communicate and contextualize data. It highlights important changes, patterns and trends using a visual format, such as charts, graphs, maps and plots, to help make data easier to understand.
How is data visualization and reporting handled in Microsoft Power BI?
In Microsoft Power BI, data visualization and reporting is a key feature that allows users to create powerful visualizations and reports that can convey complex information in an easy-to-understand format.
With Power BI, you can use charts, graphs, tables, and maps to display data and communicate insights. The platform also provides a range of tools and features to help you create interactive reports and dashboards that can be shared with others.
Additionally, the Power Bi has built-in AI-powered insights that can help you identify patterns and trends in your data, even if you don’t have any data science expertise.
Image source: Power BI
If you want to get some inspiration of amazing visualizations you can make with Power Bi, check out: Microsoft Power BI Community: Data Stories Gallery
How is data visualization and reporting handled in Amazon QuickSight?
QuickSight offers a range of visualization tools, including bar charts, line charts, scatter plots, pie charts, and tables, that allow users to create custom visualizations that best suit your needs.
QuickSight also provides a range of reporting features, including the ability to create dashboards, which are interactive reports that display multiple visualizations in a single view, making it easier for users to compare and contrast data.
Additionally, QuickSight allows users to share their visualizations and reports with others, either through email or by embedding them in other applications, so that everyone can have access to the same data-driven insights
Image source: Amazon QuickSight Documentation
Recommendation: Power BI vs AWS QuickSight for Data Visualization and Reporting
I would recommend Microsoft Power BI for data visualization and reporting. Power BI offers a wide range of features and tools to create interactive visualizations and reports, including custom visualizations and the ability to incorporate external data.
It also has a user-friendly interface and a robust community of users and developers (https://community.powerbi.com/), which makes it easier to find support and resources. Additionally, Power BI integrates well with other Microsoft products like Excel and SharePoint.
While Amazon QuickSight also has some powerful visualization and reporting capabilities, it is generally less feature-rich and more limited in its integrations compared to Power BI.
3. Power BI vs Amazon QuickSight: Machine Learning Capabilities and Integration
The use of business intelligence with machine learning can really help us make better and more efficient use of your data. By automating data processing and analysis, identifying patterns and trends, and predicting future outcomes, you can gain a competitive advantage with machine learning.
How does machine learning work in Microsoft Power BI?
Power BI has built-in machine learning capabilities that allow users to create predictive models based on their data. These models can be used to forecast future trends, detect anomalies or outliers, and classify data into different categories. Power BI also has pre-built machine learning models that can be easily integrated into reports and dashboards.
To use machine learning in Power BI, users first need to connect their data sources and import the data into the tool. They can then use the built-in machine learning features to create models and analyze the data.
Power BI also supports popular machine learning languages and frameworks such as Python and R, which can be used to create custom models and integrate them into Power BI reports.
Machine Learning in Power BI is something Microsoft is investing and focusing on so this offering will only get better and be a more and more natural part of the Power BI.
Below is an example of Purchase Intent Prediction model
Image source: Microsoft Power BI Learn
How does machine learning work in Amazon QuickSight?
Amazon QuickSight integrates with Amazon SageMaker to provide machine learning-powered insights. With SageMaker integration, you can easily build and deploy machine learning models to analyze your data and generate insights.
Amazon QuickSight uses machine learning (ML) to help users make data-driven decisions. Specifically, it applies ML algorithms to large amounts of data to identify patterns, predict future outcomes, and recommend actions based on the data.
This allows QuickSight users to go beyond basic descriptive and diagnostic analysis and move into forecasting and decision-making with confidence. QuickSight’s ML capabilities include natural language processing, anomaly detection, and forecasting, among others.
By leveraging machine learning, Amazon QuickSight makes it easier for users to understand their data and make more informed decisions.
Image source: Amazon Web Services (AWS) Machine Learning
Recommendation: Power BI vs AWS QuickSight for using Machine Learning in BI
My recommendation for machine learning integration and tools would be Microsoft Power BI. Power BI has a more advanced machine learning integration than Amazon QuickSight, providing a wide range of machine learning algorithms and techniques for advanced analytics.
With Power BI, you can use Azure Machine Learning to create and train models that can be used within Power BI for data analysis and prediction. Power BI also offers advanced analytics features, including R and Python scripting, which allow for more complex data manipulation and analysis.
Overall, both Amazon Quicksight and Microsoft Power BI are great options for business intelligence with machine learning, but in my experience, Power BI offers more advanced features and a larger user community.
4. Power BI vs Amazon QuickSight: Collaboration and Sharing Capabilities
Simply put, how easy and supportive are the tools of collaboration and sharing dashboards, reports and projects with others. Data democratization, is the process of creating a data-driven culture where business intelligence data is accessible to all users within an organization, is one of our top trends in Business Intelligence.
How is collaboration in Microsoft Power BI?
Collaboration in Microsoft Power BI is made easy with the ability to work together in workspaces, share dashboards and reports with your team.
As most have probably got familiar with Microsoft Teams, it is a collaboration tool that integrates well with Power BI and allows you to easily find data, use fully-featured experiences without leaving Teams, and bring data and insights into the collaboration platform.
By sharing reports, dashboards, and scorecards from your workspace or another workspace, you can distribute the data to coworkers to help make informed business decisions
How is collaboration in Amazon QuickSight?
Amazon QuickSight offers collaboration and sharing capabilities to help you work with others. You can easily share your dashboards and reports with others, collaborate on projects, and provide access to your data.
Recommendation: AWS QuickSight vs Power BI for Collaboration and Sharing
Ultimately, it depends on the other tools you are using. If you are working extensively with the Microsoft offering, example Teams, then Power BI integrates very well and seamlessly with other Microsoft apps.
On the other hand, if you are familiar with and using Amazon Web Service (AWS) apps, then QuickSight is easier to integrate into your current setup.
But on a general note, I would recommend Microsoft Power BI over Amazon QuickSight for collaboration and sharing capabilities. One of Power BI strengths is its collaborative features, which enable you to work together in workspaces to create meaningful reports and dashboards.
From my experience, collaboration in Power BI is easier and smoother than in QuickSight. Not that collaboration in QuickSIght is poor, it’s also good, it’s just that I think that Power BI is better in that area.
5. Power BI vs Amazon QuickSight: Pricing
Depending on who you ask, perhaps the most important aspect – what is the cost of the business intelligence tool.
What is the price of Microsoft Power BI?
There are three alternatives for Microsoft Power BI
- Free (also called Power BI Desktop)
Power BI has two main licensing options: Power BI Pro and Power BI Premium. Power BI Pro is priced per user, per month. The Power BI Premium option, however, not only has pricing per user per month, but also has a second pricing option called “per capacity”.
Image source: Microsoft Power BI Pricing
Power BI Free
Power BI Free (also known as Power BI Desktop) allows you to utilize the majority of the tools that Power BI Service provides. One of the biggest differences you’ll see when you look at Power BI Free vs Pro/Premium is that the Power BI Pro license really levels up the content sharing and collaboration options with other Power BI users
This means that creating data connections, transforming the data, and building dashboards and reports can now be a team effort.
Power BI Pro: $9.99 per user per month
The biggest difference between Free and Pro is that with Pro you can share your data, reports, and dashboards with other users who also have a Power BI Pro license. In addition, it allows connecting to numerous on-premises datasets and setting automatic refresh for these datasets.
Key differences between Pro and Free are:
- Sharing and collaboration
- Improved data refreshes
- On-premise data gateways
I would say that if you want to share data, reports, and dashboards privately – you need to look at Power BI Pro. It allows you to share your data with individual coworkers or publish enterprise-wide “content packs” and “apps” with row-level data security
Power BI Premium: $20 per user per month
Power BI Premium includes all of the features available in Power BI Pro and offers a few additional features to users. Premium is targeted towards large enterprise deployments and workloads.
Power BI Pro vs Premium
What ultimately separates the Pro and Premium versions is performance and storage. From my experience and understanding, Pro is preferable for those who want to create and share their content internally while Premium is best for those who want to share their content externally from the organization
For instance, Power BI Premium (per user) license holders have the possibility to create paginated reports, a model size limit of 100 GB (versus 1 GB for Power BI Pro users), the ability to refresh datasets 48 times per day (versus 8 for Power BI Pro users, and access to some of the more advanced and technical features in Power BI.
What is the price of Amazon QuickSight?
QuickSight is priced on a per-user basis and ranges from
- Reader: $5 per month
- Author: $28 per month
If a user goes a month without logging in, they pay nothing.
QuickSight Author is a user who can connect to data sources (within AWS or outside), create visuals and analyze data. Authors can create interactive dashboards using advanced QuickSight capabilities such as parameters and calculated fields, and publish dashboards with other users in the account
QuickSight Reader is a user who consumes interactive dashboards. Readers can only view reports and dashboard, not build and configure them. This means that readers can view shared dashboards, filter data, drill down to details or export data as a CSV file.
Want to see how Amazon QuickSight compare to Tableau? See our comparison where we discuss the key differences between the two platforms and give recommendations, including their data source compatibility, data visualizations, collaborations, pricing, and advanced features.
Conclusion and Recommendation: Power BI vs QuickSight
In conclusion, both Microsoft Power BI and Amazon QuickSight are powerful business intelligence platforms with their own unique features and strengths. Power BI is a more mature platform with a wider range of features and integrations, while QuickSight is more affordable and offers better scalability for larger organizations.
Recommendation: QuickSight vs Power BI
When choosing between the two platforms, it’s important to consider your specific business needs, budget, and level of technical expertise. If you’re looking for advanced data visualization capabilities and are willing to invest in a more established platform, Power BI may be the better choice. On the other hand, if you’re a small to mid-sized business with limited resources and want a more cost-effective option that can scale with your needs, QuickSight may be the better option.
Overall, both platforms are great choices for businesses looking to improve their data analysis and reporting capabilities. By understanding the key differences between these two platforms, you can make an informed decision about which one is right for your business.
Definition of Business Intelligence
Business Intelligence (BI) is a technology-driven process of analyzing and visualizing data to extract valuable insights and inform decision-making. It involves the use of various tools and techniques to collect, store, and analyze data, and then presenting it in an easy-to-understand format.
FAQ: AWS QuickSight vs Power BI
What are the key differences between Amazon QuickSight and Microsoft Power BI?
Amazon QuickSight is a cloud-based BI platform that focuses on providing users with fast, interactive visualizations and data exploration capabilities. u003cbru003eu003cbru003eOn the other hand, Microsoft Power BI offers a more comprehensive solution that includes data preparation, modeling, visualization, and sharing. u003cbru003eu003cbru003ePower BI also integrates with other Microsoft products, such as Excel and SharePoint, making it a good fit for organizations already using the Microsoft ecosystem.
Which platform offers more advanced data visualization features?
Both platforms offer robust data visualization features, but Microsoft Power BI has a more extensive set of visualization options, including custom visuals created by the Power BI community. Power BI also offers more advanced data modeling and analysis capabilities.
How does the pricing of Power BI compare to Amazon QuickSight?
Power BI and QuickSight have different pricing models. QuickSight charges per user per month, with a separate cost for data access. u003cbru003eu003cbru003ePower BI, on the other hand, offers a range of pricing plans, including a free version, a per-user subscription, and an enterprise plan. The pricing for Power BI varies based on the number of users and the features required.
Can both Amazon QuickSight and Microsoft Power BI connect to the same data sources?
Both platforms can connect to a wide variety of data sources, including popular cloud-based solutions like Amazon Redshift, Google BigQuery, and Microsoft SQL Server. u003cbru003eu003cbru003eHowever, some sources may be better supported on one platform than the other, so it’s important to check the list of supported data sources before making a choice.
What kind of support and training resources are available for Microsoft Power BI and Amazon QuickSight?
Both platforms offer a range of support and training resources, including documentation, online forums, and video tutorials. Microsoft also provides paid support options for Power BI users. u003cbru003eu003cbru003eAdditionally, Power BI has a strong community of users who create and share custom visuals and other resources. QuickSight, on the other hand, has fewer community resources available but provides access to Amazon’s extensive support network.