Dataiku Data Science Studio Review

User interface is colorful, beautiful, and well-designed but sometimes the solution can be slow


What is our primary use case?

I just use the product for data migration. Once a month, I push data from one Redshift data warehouse to another Redshift data warehouse. I do that by using a simple SQL query.

What is most valuable?

I like the interface, which is probably my favorite part of the solution. It is really user-friendly. I might think that it is user-friendly because I'm in IT and it seems familiar to me. It is colorful and I think it is really beautiful and well-designed.

What needs improvement?

I think the interface is very nice, but for somebody who is not as familiar with IT as I am, it may be much more difficult for them. It is nice for me because I'm familiar with this type of software that falls in the realm of the data science platform. I can see how a client who really doesn't know anything about IT or computers might try to use it and find that it would be a little difficult to access some features. That type of user may really need training in order to work with Dataiku. So, in the next release of Dataiku DSS (Data Science Studio), they should make it more friendly for everybody to use, not just IT people. 

For me, I find that it is a little slow during use. When I use Dataiku to run my script to transfer data, it takes more time than I would expect for the operation to complete.

For how long have I used the solution?

I have been using this solution for a year.

What do I think about the stability of the solution?

I have not done a lot of exploration into Dataiku and its other features as I only use it for a particular task. But from my experiences and from the review I'm seeing online, it is a stable solution.

What do I think about the scalability of the solution?

I think there is some room for improvement in scalability as I already find it performs a little slowly. In my company, there are three of us. There is an IT manager, there is the data warehouse manager, and there is me. In the company that we use it for, there are more than 800 employees.

How are customer service and technical support?

I have contacted customer service before. They respond quickly, so that is a plus.

Which solution did I use previously and why did I switch?

We did not use other solutions before switching so much as we are using a few different solutions together. We use Knime and Alteryx for data science and analytics. I just use Dataiku for data migration for now. I just started using Knime, but I'm most familiar with Alteryx because I have used it for one-and-a-half-years to practice ATL (Active Template Library) on my data. Alteryx is somewhat the same as Knime, but it is more user-friendly.

How was the initial setup?

The company I work for did the setup for me. It was already set up when I came.

What about the implementation team?

We are consultants so we do the implementations ourselves. Another consultant introduced Dataiku to us initially. I guess they really appreciated the solution.

What other advice do I have?

Dataiku is a very broad solution that offers many possibilities. If you want to use it you must be fully committed to it. 

The biggest lesson I learned from using the product is that you can do many things with it. But you must commit the time to discover the tool.

On a scale from one to ten where one is the worst and ten is the best, I would rate Dataiku as a seven. It is a little bit of a conservative rating because it is a nice solution and I just use it for a particular task.

Which deployment model are you using for this solution?

Private Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Amazon Web Services (AWS)
Disclosure: My company has a business relationship with this vendor other than being a customer: Partner.
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