We performed a comparison between CloverETL and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Tableau, Qlik, Splunk and others in Data Visualization."Server features for scheduler: It is very easy to schedule jobs and monitor them. The interface is easy to use."
"Connectivity to various data sources: The ability to extract data from different data sources gives greater flexibility."
"Key features include wealth of pre-defined components; all components are customizable; descriptive logging, especially for error messages."
"No dependence on native language and ease of use."
"It provided the capability to visualize a bunch of data in an organized way."
"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."
"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 alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."
"It integrates well with SAS, making it simple and quick for developers."
"It's relatively simple to create basic dashboards and reports."
"It's a stable, reliable product."
"Needs: easier automated failure recovery; more, and more intuitive auto-generated/filled-in code for components; easier/more automated sync between CloverETL Designer and CloverETL Server."
"Resource management: We typically run out of heap space, and even the allocation of high heap space does not seem to be enough."
"Its documentation could be improved."
"The licensing ends up being more expensive than other options."
"A bit more flexibility in the temperatization will be helpful."
"The charts and tables could use better sorting, primarily using other variables than the ones on the figure. If they could implement views like in the older version (previous to Viya), it would be very nice."
"There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data."
"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."
"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."
"The solution should improve its graphics."
"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."
Earn 20 points
CloverETL is ranked 41st in Data Visualization while SAS Visual Analytics is ranked 7th in Data Visualization with 35 reviews. CloverETL is rated 7.0, while SAS Visual Analytics is rated 8.0. The top reviewer of CloverETL writes "Provides wealth of pre-defined, customizable components, and descriptive logging for errors". On the other hand, the top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". CloverETL is most compared with iWay Universal Adapter Framework, Talend Open Studio and SSIS, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and Dataiku Data Science Studio.
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We monitor all Data Visualization 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.
