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."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."
"Data Science Studio's data science model is very useful."
"The solution is quite stable."
"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."
"The most valuable feature is the set of visual data preparation tools."
"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."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Simplifies report designs and quickly displays tables and graphs."
"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 flexibility of the configuration is valuable to me."
"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."
"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."
"We've found the product to be stable and reliable."
"Quick deployment to dashboards and analytics features (using SAS Visual Statistics and Enterprise Guide). Easy to create a simple forecast and discover business insights using segmentation tools."
"The alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."
"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."
"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."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"I think it would help if Data Science Studio added some more features and improved the data model."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"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 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 is a need for coding when it comes to digital reporting which can be intimidating."
"Colours used on report objects"
"SAS Visual Analytics could be more user-friendly."
"A bit more flexibility in the temperatization will be helpful."
"The solution is a little weak at the front end."
"The product is expensive and needs the integration of more languages."
"It is not as mature as competitors such as Tableau and QlikView."
"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."
Dataiku is ranked 7th 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 H2O.ai, 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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