Dataiku Data Science Studio Pros and Cons

Dataiku Data Science Studio Pros

ManuelaGhomsi
Business Intelligence Developer/ Data Scientist at a tech services company with 11-50 employees
I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person.
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Giuseppe-Naldi
Principal Full Stack Data Scientist at ICTeam
The most valuable feature is the set of visual data preparation tools.
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Abhik Chakraborty
Senior Business Technology Analyst at a consultancy with 5,001-10,000 employees
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.
Cloud-based process run helps in not keeping the systems on while processes are running.
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Find out what your peers are saying about Dataiku, Alteryx, Knime and others in Data Science Platforms. Updated: December 2019.
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reviewer1014468
Practice Manager Data Intelligence at a tech services company with 1,001-5,000 employees
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.
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Dataiku Data Science Studio Cons

ManuelaGhomsi
Business Intelligence Developer/ Data Scientist at a tech services company with 11-50 employees
I find that it is a little slow during use. It takes more time than I would expect for operations to complete.
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Giuseppe-Naldi
Principal Full Stack Data Scientist at ICTeam
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.
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Abhik Chakraborty
Senior Business Technology Analyst at a consultancy with 5,001-10,000 employees
Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable.
Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days).
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.
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Find out what your peers are saying about Dataiku, Alteryx, Knime and others in Data Science Platforms. Updated: December 2019.
390,810 professionals have used our research since 2012.
reviewer1014468
Practice Manager Data Intelligence at a tech services company with 1,001-5,000 employees
The ability to have charts right from the explorer would be an improvement.
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Find out what your peers are saying about Dataiku, Alteryx, Knime and others in Data Science Platforms. Updated: December 2019.
390,810 professionals have used our research since 2012.