Amazon QuickSight Reviews

Amazon QuickSight demonstrates high scalability, and this gives us a clear dashboard that supports data visualization

The program has a favorable pricing model that makes it cost effective and preferable

We have no complexities in integrating the program with other AWS services and this supports comprehensive analytics, even with large datasets

The program has minimal set up requirements and no extra infrastructure deployment that is needed

What I like most about Amazon QuickSight is how quickly it can analyze large datasets without requiring a heavy setup. The SPICE engine helps keep dashboards fast and responsive, even when workloads get complex. I also appreciate its native integration with AWS services, which streamlines the analytics pipeline and makes data ingestion and automation feel effortless. The interface is intuitive, so it’s easy to build clean, insightful visualizations in just a few minutes. With its fully serverless architecture, QuickSight also removes much of the maintenance overhead and scales automatically, which makes it a reliable and efficient BI solution for modern data teams.

What I dislike about Amazon QuickSight is that some advanced configuration options feel buried, so fine-tuning complex dashboards can take longer than it should. The flexibility around custom visuals and layout is still limited compared with more mature BI tools, which can make it harder to produce highly tailored reports. The learning curve can also be steep for non-technical users, particularly when you’re integrating multiple AWS data sources. Pricing can become less predictable at scale as well, especially if SPICE capacity needs to be expanded frequently. Overall, it’s a powerful platform but can feel rigid at times, especially for teams that need deep customization and fully polished, enterprise-grade dashboards.

Amazon QuickSight addresses slow, fragmented reporting by giving me a single, scalable BI layer that connects directly to my AWS data sources. It reduces the need for manual data preparation with SPICE, which speeds up queries and keeps dashboards responsive, even when working with large datasets. Its serverless architecture also removes much of the infrastructure overhead, so I don’t have to manage clusters or worry about capacity planning. By centralizing dashboards, automating refreshes, and integrating smoothly with the rest of AWS, QuickSight helps me deliver insights faster while lowering the operational effort needed to maintain my analytics workflows.

ease of use and reliability on huge amounts of data. There are a lot of personalised use cases for which we've built dashboards on Quicksight that is really helpful.

nothing as such, so far it has helped us as much as we want. i use it for revenue, spends tracker, retention dashboards, geography level performance and all of it is up to the mark

everything related to data- data wrt daily performance of all geographies, split across different date diffs, platform leve, media source level, age, gender and a lot of other splits.

New features have been added to Amazon QuickSight, including the new QuickSuite UI. Features like chat/AI search make it easier to learn more about reports, and they help users a lot. Even when there are gaps that weren’t explained in the analysis, it becomes easier for business stakeholders to review and understand the report. This new compatibility with the AI chatbot is great. The new charts that have been added also give more exposure and encourage me to explore QuickSight more as a tool. A lot of seminars have also happened to build more awareness, so overall it feels like a great community.

It still feels limited due to the lack of customization options. I also feel it has fewer chart types than I need, and it could include more chart options overall. Sometimes, depending on the data size, the Spice engine refresh is a bit slow and takes time.

Earlier, I used Metabase as a reporting tool. After that, I switched to QuickSight for a smaller number of reports. Later, we completely migrated all reports to QuickSight because it integrates easily with our DW. Also, more direct data sources are now available in QuickSight, which makes things easier as well. From time to time, new features get added, which is helpful.

.The thing I like about this Is it’s server less, fast and integrates easily with AWS, and it let me create intractive dashboard and I get AI based insights without any heavy setup

The only thing I disklike about quick sight is that the visual customization and advanced features are limited and something it’s difficult for me to understand some features in it

The thing

I can create charts and dashboards easily, and it integrates with Redash. It also lets me create calculated columns and metrics, and everything can be updated based on live data.

Downloading data is a bit slow. For example, downloading around 400 MB can take more than 10 minutes. The UI could also be more interactive, and the query language feels a bit different from standard PostgreSQL or MySQL.

We

Allows me to use AI to generate answers based on my company standard operating procedures. Previous ai chat bots were inaccurate or would not display the correct answer, but Quicksight is much better

Very difficult to set up ai chatbot. I needed to request the help of Amazon IT and took several months to create and use the ai chatbot and another month providing and validating the information generated.

Is able to generate answers for many common questions for Amazon project managers onsite for deploying new buildings.

It is a cloud-based business intelligence and data visualization service that helps the company to analyze data, create dashboards, and share insights. It has a fast in-memory engine to process data quickly even with larger data sets. Its interface is easy to use and easy to implement.

It is limited pre-built visualizations compared to other tools; its initial setup is complex and complicated. The data transformations are limited. Its customer service is also not that strong.

As a product designer it has helped me to visualize and interpret data from multiple sources, by which it can deliver real-time insights that allow better decisions. It has also helped in optimizing user experience with automated reports serving as a self-serving insight.

Ease of connection with source data and view datasets. Once connection is done with source data can create variety of multiple graphs and charts quickly with drag and drop functionality.

User interface need to work to get more user friendly other than that all things are good.

If we compare with the other tools then can be improved on UI.

Data to extract from Athena and visualize on QuickSight, Action perform for some visual not all so in short customize action on visuals which benefits me.