We performed a comparison between SAS Visual Analytics and Tableau based on real PeerSpot user reviews.
Find out in this report how the two Data Visualization solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."I believe that the possibilities for exploring data and formulating visual results are quite good because it allows the business analyst to have different perspectives on the data."
"The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced technologies such as machine learning and artificial intelligence. This helps with quality assurance processes."
"The flexibility of the configuration is valuable to me."
"It's quite easy to learn and to progress with SAS from an end-user perspective."
"What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes."
"It integrates well with SAS, making it simple and quick for developers."
"It's relatively simple to create basic dashboards and reports."
"The product is stable, reliable, and scalable."
"Tableau has many different connectors for different databases. It's very easy to connect to MySQL, SQL Server, Amazon EMR, Presto, Redshift, BigQuery, and so on."
"The most valuable features of the solution are the permission management and the user management."
"It's very easy to use and users don't need any IT support to access it as the information is right there."
"Technical support has been responsive."
"It is definitely easy to use. It is intuitive, and more or less, everything can be done from the front end. As such, there is no concept of metadata. You can just take data from a database and start building your own stuff, such as OLAP data warehouse. You don't need extensive metadata modeling like Oracle BI."
"I like Tableau's heat maps and the storyboard. You can create data stories and tons of visuals with it, and it goes together really well. Tableau lets you manipulate the data in various ways."
"It has a shallow learning curve and so you can go to market very, very, very quickly."
"The best use case for us is the solution's integration with Salesforce because we are also partners of Salesforce."
"There is room for improvement in anti-money laundering prevention and operation monitoring, as well as operation monitoring surveillance."
"There is a need for coding when it comes to digital reporting which can be intimidating."
"The installation process can be a bit complex."
"The product is expensive and needs the integration of more languages."
"The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."
"There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else."
"The licensing ends up being more expensive than other options."
"SAS Visual Analytics could be more user-friendly."
"Include forecasting on table calculation fields."
"Areas for improvement would be visualization and augmented analytics. In the next release, I would like to see automated insights from the data added to the dashboard."
"It should offer better features for customization."
"The forecasting feature in Tableau in my view is too limited because it must have dates but I should be able to predict the outcome of an event without having a date as part of the input."
"The customization requires a lot of effort and should be simplified. The performance could be better."
"The integration with other program languages, like Python, needs to be better."
"With Tableau, there is a gap in its ability to handle very large-scale data."
"More integration with Python or something related to machine learning would be a good improvement."
SAS Visual Analytics is ranked 7th in Data Visualization with 9 reviews while Tableau is ranked 1st in Data Visualization with 18 reviews. SAS Visual Analytics is rated 8.0, while Tableau is rated 8.4. The top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". On the other hand, the top reviewer of Tableau writes "Provides fast data access with in-memory extracts, makes it easy to create visualizations, and saves time". SAS Visual Analytics is most compared with Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio, Dataiku Data Science Studio and SAS Enterprise Miner, whereas Tableau is most compared with Microsoft Power BI, Amazon QuickSight, Domo, SAP Analytics Cloud and Databricks. See our SAS Visual Analytics vs. Tableau report.
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It totally depends on what SAS licensing are in place. Tableau provides integration with R as far as I know.
These products all do more or less the same things but often in a very different way. The differences that I am able to report are mainly:
-Look and feel and here Tableau is definitely superior.
-Usability, both on the user and developer side and here the products are not very far apart, I would say Tableau a little better.
-Managed data volumes and here SAS is unmatched (in Unicredit I have seen an installation that serves about 11000 users).
Tableau is a great tool for visual analytics but when it comes to statistical analysis, it has limited features. You can find basic descriptive statistics like mean, median, mode, SD, Skewness, Kurtosis, etc but for advanced statistical analysis, you can have machine learning models too along with advanced forecasting. If your work does not involve advanced statistical analysis then Tableau is a great tool for basic statistical analysis. In case you have further doubts, please feel free to ask.