Qrvey vs. SAS Visual Analytics

Qrvey is an excellent solution for AWS-based customers looking to add embedded analytics functionality. It is cloud-native and good at scaling. There are BI solutions with greater depth in particular areas (chart types, custom metrics), but Qrvey has an unmatched level of customizability for embedded use cases. Many APIs are also exposed and documented, making them easy to integrate into a data ecosystem.

Incentivized

I was in a meeting with the client and there I have to show them some analytic data to them. But I was confused about how I will manage to show big data to clients with accuracy. But then the SAS Visual Analytics software helps me in presenting accurate data at the moment and it was very presentable and through that, I got the deal for that business.

Incentivized

• The platform deploys to our AWS instance which gave us the ability to manage ourselves
• The feature of easily embedding visualizations into other applications
• The powerful features like workflow automation

• Provides the flexibility to the end user to slice and dice the data.
• Anyone can make predictive models with the help of in-built algorithms without the need to write a single line of code or knowledge of what's under the hood of algorithms.
• The feature to simply ask a question related to data and getting a response in form of text, chart or graph is amazing.

Incentivized

• Merges between heterogenous datasets can occasionally be problematic
• The dashboards/pages are already very powerful, but more interactive elements would always be welcome.
• The administration of a Qrvey instance and underlying datastore can sometimes be complex, but the Admin app helps make this a smooth process.

Incentivized

• SAS is relatively expensive when compared to other BI tools and requires a large amount of upfront fee which becomes an issue for smaller organizations.
• UI for the dashboards looks a little date in comparison to competitors like Tableau and Microstrategy.
• Integration with other open source software like Python needs to be built in.

Incentivized

SAS really is the cutting edge in Business Intelligence. That is all they do! They are constantly coming out with new products, product upgrades, and their tech support is second to none. In addition, their support of Education has made our ability to acquire their product possible.

SAS BI is good for creating reports and dashboards and then sharing it with the users. It also has ability to manage access to the reports and dashboards but somehow with most of the world moving to open source languages R, Python and Julia, SAS BI feels to be archaic in terms of feature set and integrations it allow[s]. Also, comparing it with other Business Intelligence tools like Tableau and Microsoft BI, the functionality of SAS BI is very limited and doesn't justify the pricing.

Incentivized

When you call tech support, you are immediately routed to a person who can answer your question. Often they can answer on the spot. However, if they cannot, you are given a track number and then followed up with. There have been times when I have had multiple track numbers open and they will actually TRACK YOU DOWN to ensure that your problem has been resolved. Issues do not fall into black holes with SAS. They are also willing to do a WebEx with you to diagnose the problem by seeing your environment, which is always helpful.

SAS Business Intelligence is not the cream of the crop for business intelligence applications, but it is not far behind. The software is generally easier to apply than most other business intelligence software. Additionally, SAS Business Intelligence runs smoothly in the background when making real-time updates. With that said, the software is not as efficient of many of the other business intelligence software applications that have been on the market for longer than this one.

Incentivized

• In one implementation, Qrvey helped our customer quickly achieve feature parity with competitors, reducing churn.

Incentivized

• SAS Visual Analytics licensing cost should be reduced to enable users to use it in mass scale.
• More statistical and mathematical equations and theories should be converted into SAS functions for reusing.
• Because of enriched ETL and reporting capabilities SAS Visual Analytics is most preferred by business users.

Incentivized