We performed a comparison between Dataiku and SAS Visual Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Databricks, Microsoft, Alteryx and others in Data Science Platforms."Data Science Studio's data science model is very useful."
"The most valuable feature of this solution is that it is one tool that can do everything, and you have the ability to very easily push your design to prediction."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"The solution is quite stable."
"Extremely easy to use with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors."
"The most valuable feature is the set of visual data preparation tools."
"Visual Analytics is very easy to use. I use Visual Analytics for all the typical use cases except text mining. I used it to analyze data and monitor statistics, not text mining. I also use it for data visualization as well as creating interactive dashboards and infographics."
"The technical support services are good."
"It's a stable, reliable product."
"It's relatively simple to create basic dashboards and reports."
"I use Visual Analytics for enterprise reporting."
"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."
"We've found the product to be stable and reliable."
"The product is stable, reliable, and scalable."
"I think it would help if Data Science Studio added some more features and improved the data model."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"The ability to have charts right from the explorer would be an improvement."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"In the next release of this solution, I would like to see deep learning better integrated into the tool and not simply an extension or plugin."
"The interface for the web app can be a bit difficult. It needs to have better capabilities, at least for developers who like to code. This is due to the fact that everything is enabled in a single window with different tabs. For them to actually develop and do the concurrent testing that needs to be done, it takes a bit of time. That is one improvement that I would like to see - from a web app developer perspective."
"There were stability issues: 1) SQL operations, such as partitioning, had bugs and showed wrong results. 2) Due to server downtime, scheduled processes used to fail. 3) Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders."
"The licensing ends up being more expensive than other options."
"The solution is a little weak at the front end."
"SAS Visual Analytics could improve by making it more accessible for users outside the organization."
"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 visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."
"There is room for improvement in anti-money laundering prevention and operation monitoring, as well as operation monitoring surveillance."
"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."
"It is not as mature as competitors such as Tableau and QlikView."
Dataiku is ranked 11th in Data Science Platforms with 7 reviews while SAS Visual Analytics is ranked 8th in Data Visualization with 36 reviews. Dataiku is rated 8.2, while SAS Visual Analytics is rated 8.2. The top reviewer of Dataiku writes "Gives different aspects of modeling approaches and good for multiple teams' collaboration". On the other hand, the top reviewer of SAS Visual Analytics writes "Single environment for multiple phases saves us time, and has good visualizations". Dataiku is most compared with Databricks, KNIME, Alteryx, RapidMiner and Domino Data Science Platform, whereas SAS Visual Analytics is most compared with Tableau, Microsoft Power BI, Databricks, Microsoft Azure Machine Learning Studio and SAS Enterprise Miner.
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