Microsoft Power BI and Amazon QuickSight compete in the business intelligence tools category, offering data visualization and analytics capabilities. Power BI stands out due to its deep integration with Microsoft products and extensive feature set.
Features: Power BI offers deep integration with Microsoft products, rich data transformation capabilities, and robust support for a wide range of data sources. QuickSight provides seamless integration with AWS services, ease of use, and advantageous pay-as-you-go pricing for AWS users.
Room for Improvement: Power BI could enhance real-time data processing, improve integration with other cloud services, and make usability more non-technical-friendly. QuickSight should expand advanced visualization options, enhance enterprise-level features, and improve integration with non-AWS platforms. Additionally, QuickSight could benefit from better user guidance.
Ease of Deployment and Customer Service: Power BI offers versatile deployment options including public, private, and hybrid cloud environments, with robust customer support and extensive online resources. QuickSight is cloud-based, easy for AWS users, but less flexible in on-premises setups, relying on AWS support channels.
Pricing and ROI: Power BI is competitively priced, especially against Tableau and QlikView, offering a substantial ROI with its comprehensive features. It has a free version upgradeable per needs. QuickSight’s pay-as-you-go model is cost-effective for AWS but can become costly with high usage. Although attractive to AWS users, Power BI offers better value with advanced functionalities for a wider range of features at a competitive price.
In a world surrounded by data, tools that allow navigation of large data volumes ensure decisions are data-driven.
Power BI is easy to deploy within an hour, providing robust security against data leaks.
I would say out of all the support experience I've had, only 5% took quite a long time to respond to the support message.
The significant drawback I notice is that Microsoft's size makes it hard to get specific change requests addressed unless they involve a bug.
We have a partnership with Microsoft, involving multiple weekly calls with dedicated personnel to ensure our satisfaction.
The support is good because there is also a community available.
You expect only a small percentage of users concurrently, but beyond a thousand concurrent users, it becomes difficult to manage.
With increasing AI capabilities, architectural developments within Microsoft, and tools like Fabric, I expect Power BI to scale accordingly.
As more data is processed, performance issues may arise.
In terms of stability, there's no data loss or leakage, and precautions are well-managed by Microsoft.
We typically do not have problems with end-user tools like Excel and Power BI.
It is very stable for small data, but with big data, there are performance challenges.
Understanding how AWS charges for Amazon QuickSight usage is critical for all users wanting to visualize their data effectively.
For example, making automation for filling missing data or reformatting incorrect data formats, and making date corrections.
This makes Power BI difficult to manage as loading times can reach one or two minutes, which is problematic today.
Access was more logical in how it distinguished between data and its formatting.
Microsoft updates Power BI monthly based on user community feedback.
It is not expensive, but it is also not cheap.
I found the setup cost to be expensive
Power BI isn't very cheap, however, it is economical compared to other solutions available.
The pricing for Microsoft Power BI is low, which is a good selling point.
The natural language query is very important, and natural language processing is crucial for disseminating dashboards across multiple formats and mechanisms.
You can measure the progress of sales, and you can measure the weakness or lowest activity of sales in some areas and determine how to improve it.
In today's data-driven environment, these tools are of substantial value, particularly for large enterprises with numerous processes that require extensive data analysis.
Within the organization, Microsoft Power BI is used to create dashboards and gain insights into data, enhancing data-driven decision-making.
To reduce the need for highly skilled personnel, we can engage someone who is just familiar and has a basic understanding of Microsoft Power BI, while AI can handle the major tasks through either agent AI or requirement analysis.
| Product | Market Share (%) |
|---|---|
| Microsoft Power BI | 12.7% |
| Amazon QuickSight | 4.5% |
| Other | 82.8% |
| Company Size | Count |
|---|---|
| Small Business | 7 |
| Midsize Enterprise | 10 |
| Large Enterprise | 14 |
| Company Size | Count |
|---|---|
| Small Business | 134 |
| Midsize Enterprise | 57 |
| Large Enterprise | 165 |
Amazon QuickSight is a fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. Using our cloud-based service you can easily connect to your data, perform advanced analysis, and create stunning visualizations and rich dashboards that can be accessed from any browser or mobile device.
Microsoft Power BI is a powerful tool for data analysis and visualization. This tool stands out for its ability to merge and analyze data from various sources. Widely adopted across different industries and departments, Power BI is instrumental in creating visually appealing dashboards and generating insightful business intelligence reports. Its intuitive interface, robust visualization capabilities, and seamless integration with other Microsoft applications empower users to easily create interactive reports and gain valuable insights.
We monitor all BI (Business Intelligence) Tools reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
