AWS Analytics Reviews

Stochastic integration with AWS is QuickSight's best feature in my opinion, joined by its very cheap pay-per-session pricing and one of the most user-friendly interfaces. Therefore, with the natural language query (QuickSight Q), it makes data analysis fast and easy, while large datasets are handled smoothly, with great scalability. An ideal choice for AWS-centric people. Review collected by and hosted on G2.com.

It can be disappointing to see the broad customization options provided by other vendors-for instance, Tableau or Power BI-not being extended to Amazon QuickSight in areas of visualization or dashboard customization. Very large datasets may slow down performance; complex queries generally cause difficulties; and integration with non-AWS data sources sometimes requires extra effort, though AWS definitely has a lot of built-in connectors. Besides, basic features are easy to learn, but advanced features like calculated fields or custom SQL queries have a steep learning curve in that it may take weeks or months to truly master all the technicalities. Even these limits might obstruct people attempting to achieve more nicely tailored or complex analytics solutions. Review collected by and hosted on G2.com.

Quicksight has good visualization capabilities, and integrates well with AWS-hosted datasets. It offers a good entry point to BI tools, whit enough tools to put something together quickly yet effectively fairly intuitive (although some features are not so straightforward i.e. page filters)

On top of that, it does do well in access controls (both at a row and column level), and can be configured with AWS ML capabilities for alerts and annomalies.

Creating calculating fields will require a bit of learning, but easy enogh to pick up if you are familiar with other BI´s tools syntaxes.

The pricing model is flexible enough and can be a good choice for a BI tool when the use base is small. Review collected by and hosted on G2.com.

Navigating the IAM permissions can be a bit painful, and it´s prone to duplication of licenses for users (specially in multiple AWS accounts environments).

Things like filters and parameters are not the most straigthforward thing to implement, and there is little room for customization of visuals (which can feel very restrictive for advance Tableau users).

As far as I could see, there is no easy way to create ´tamplate´ dashboard to re-use/re-deploy across different AWS accounts, and if you are a PowerBI user you may really miss Power Query like tools to clean and prepare your data.

For less-technical users, there may be a bit of a learning curve that will require some SQL skills, specially if you are pulling your data from Athena views Review collected by and hosted on G2.com.

Amazon Redshift has an easy to use and setup gives teams of all sizes access to data warehousing and analytics. It’s got robust feature and it integrates well with other AWS services to make it easy to implement and scale. Their customer support is reliable and their use frequency adds a value by using their analytics which give us important insights about our business. Review collected by and hosted on G2.com.

While powerful, Amazon Redshift can be expensive to process on a large scale with increasing amount of data. Complex joins can slow down query performance, and tuning is an expertise. In high demand environments there is limited support for unstructured data and frequent optimization can be difficult, especially for daily operations. Review collected by and hosted on G2.com.

Amazon Redshift is a game-changer, allowing us to have highly scalable and performance-enabled data warehousing for the complex project. The MPP architecture and columnar storage offer powerful query performance on the platform. Redshift also allowed us easily to integrate several AWS services, such as using S3 for data imports and Glue for ETL operations, and made our pipeline very streamlined so that data transfer and queries were decreased by many times.

With Spectrum, Redshift can handle structured as well as semi-structured data, which will allow efficient cross-database queries and productivity boost with regards to data analytics and reporting. Advanced data compression features and data distribution ensure that storage is optimally utilized while efficiently making use of and managing costs on resources. Review collected by and hosted on G2.com.

Though performance and scalability of Redshift are excellent, the system is not very easy to use for optimization and query tuning for new users. Automated tools for better configuration will enable it to reach a diverse set of teams. Review collected by and hosted on G2.com.

When I think of Amazon QuickSight, the first thing that comes to my attention is the fact that it made the task of building any sort of interactive dashboards much easier compared to other tools that I had previously used for presenting data. As for my experience with QuickSight – the interface was very intuitive. That allowed me and my colleagues to interact with plenty of data that we had in our AWS ecosystem – which was very helpful and saved us a lot of headaches. Review collected by and hosted on G2.com.

At first yes, I did get the feeling that there is a lack of avenues for dashboard personalization, but the longer that I stayed with the system, the more I realized that the vast majority of our requirements can be satisfied with the provided templates. Though, I do still think that a twp or three more types of graphical representation would be meet additional needs fairly well. Review collected by and hosted on G2.com.

Whenever I need to manage large datasets, Amazon Redshift is my go-to tool. Its ability to handle complex queries and large volumes of data makes it essential for my work. The speed and efficiency with which it processes data are particularly impressive. Review collected by and hosted on G2.com.

For someone new to AWS or cloud-based data warehousing, getting started with Redshift can be a bit tricky. The initial learning curve was steep for me, especially when it came to understanding the migration process. But with time, I found it to be an invaluable platform for analyzing complex data. Review collected by and hosted on G2.com.

Most of the infrastructure, basically some configurations like monitoring the pipelines, receiving notifications or alert messages, status etc... are managed by the service provider.

Fairly an easy learning curve to build pipelines with good scaling capabilities as your data needs increase. Everything is secured and regulated with the necessary compliances too. Review collected by and hosted on G2.com.

I feel the pipelines fail or there is a downtime crash that happens sometimes. The Data Pipelines you build should be good enough to run efficiently. Takes a steep learning curve when you use it for real-time data processing as it needs a higher understanding and expertise to be able to handle that. No as fast when it comes to real-time processing. Review collected by and hosted on G2.com.

Easy to trace the error in the script through runs.

My team build a framework to fetch data from different platform through AWS Glue and stores them in S3 in the file format mention by us. That make our integration and fetching data a lot easier.

Sppourt frequent data load.

It is easy to implement.

Good customer support. Review collected by and hosted on G2.com.

Many a time I face server/connectivity issue when using glue and our job get blocked due to that.

Does not support xml file formats. Review collected by and hosted on G2.com.

I love that how easy it was to learn using this product. Amazon QS is part of the AWS ecosystem, therefore it offers seamless AWS integration with services like S3, Redshift. Review collected by and hosted on G2.com.

Our team believes this tool lacks advanced customization options for dashboards and visualizations compared to the previously used Power BI and Tableau. As we prioritize cost-efficiency, we don't use SPICE, so the data refresh rates are slower than average, especially when we are having bigger clients who need larger datasets. Review collected by and hosted on G2.com.

It provides easy to use and implement yet very powerful columns based data solution that helps in faster query performance. Also cross database analytics is gamechanger. Review collected by and hosted on G2.com.

It requires time for propely optimizing and tuning queries for the db which is the downside of this solution. Review collected by and hosted on G2.com.