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it_user837543 - PeerSpot reviewer
Senior Business Technology Analyst at a consultancy with 5,001-10,000 employees
Real User
GUI-based functionality is easy to use, but server up-time needs to be improved
Pros and Cons
  • "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."
  • "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."

What is our primary use case?

ETL development.

How has it helped my organization?

Compared to Informatica, this tool is extremely easy with its GUI-based functionality and large compatibility with various data sources. Also, maintenance processes are much more automated than ever, with fewer errors.

What is most valuable?

  • Process scheduler (called Scenario).
  • Cloud-based process run, which helps in not keeping the systems on while processes are running.

What needs improvement?

Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable.

Buyer's Guide
Dataiku
March 2025
Learn what your peers think about Dataiku. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
842,592 professionals have used our research since 2012.

For how long have I used the solution?

One to three years.

What do I think about the stability of the solution?

There were stability issues.

  • SQL operations, such as partitioning, had bugs and showed wrong results.
  • Due to server downtime, scheduled processes used to fail.
  • Access to project folders was compromised (privacy issue) with wrong people getting access to confidential project folders.

What do I think about the scalability of the solution?

Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days).

How are customer service and support?

I would rate tech support at six out of 10.

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

I have previously worked with Alteryx. I switched for these reasons: 

  • Big Data tools like Python and Hive are already supported
  • Cloud-based processing
  • Better value for money for client.

How was the initial setup?

Initial setup was done by the IT team from the client's side. No involvement in the initial setup from our side.

What's my experience with pricing, setup cost, and licensing?

Since this was a client-advised tool, no information of costs is available to us.

Which other solutions did I evaluate?

Unfortunately, no.

What other advice do I have?

Easy-to-use tool, but slightly unstable in terms of a few modules. Proceed with some amount of caution and knowledge.

Disclosure: I am a real user, and this review is based on my own experience and opinions.
PeerSpot user
reviewer1014468 - PeerSpot reviewer
Practice Manager Data Intelligence at a tech services company with 1,001-5,000 employees
Real User
An all-in-one data prediction tool that is simple to install and use
Pros and Cons
  • "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 ability to have charts right from the explorer would be an improvement."

What is our primary use case?

I use this solution to make predictions from time-series data. I am a consultant and operate this solution for my clients.

What is most valuable?

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. 

What needs improvement?

I would like to have better exclusion of data capability.

The ability to have charts right from the explorer would be an improvement.

I would like to see additions to the architecture for specific business use cases.

For how long have I used the solution?

I have been using this solution for two years.

What do I think about the stability of the solution?

This is a stable solution. I have not seen any bugs or glitches.

What do I think about the scalability of the solution?

This platform is easy to scale. You can take full advantage of your office architecture.

My client has more than twenty people using this solution.

How are customer service and technical support?

I have been in contact with technical support through the website.  They have chatbots that dispatch tickets to specific people, depending on the problem. They respond quickly and I am satisfied with the support.

How was the initial setup?

The initial setup of this solution is straightforward.

What about the implementation team?

I performed the implementation myself. By reading the documentation, it is simple.

What other advice do I have?

My advice to anybody who is implementing this solution is to use the tutorial first. There are lots of tutorials available that help to quickly explain the solution.

This is a product that I recommend.

I would rate this solution an eight out of ten.

Which deployment model are you using for this solution?

On-premises
Disclosure: My company has a business relationship with this vendor other than being a customer: Reseller.
PeerSpot user
Buyer's Guide
Dataiku
March 2025
Learn what your peers think about Dataiku. Get advice and tips from experienced pros sharing their opinions. Updated: March 2025.
842,592 professionals have used our research since 2012.
Business Intelligence Developer/ Data Scientist at a tech services company with 11-50 employees
Real User
User interface is colorful, beautiful, and well-designed but sometimes the solution can be slow
Pros and Cons
  • "I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
  • "I find that it is a little slow during use. It takes more time than I would expect for operations to complete."

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.
PeerSpot user
reviewer2667285 - PeerSpot reviewer
Big Data Consultant at a computer software company with 1,001-5,000 employees
Reseller
Drag-and-drop platform accelerates model development with distributed compute engine
Pros and Cons
  • "Our clients can easily drag and drop components and use them on the spot."
  • "There is room for improvement in terms of allowing for more code-based features."

What is our primary use case?

My company sells licenses for both Dataiku and Alteryx, and we have clients who use them. I engage with several companies in telecommunications, retail, and energy to assess how our clients are utilizing these platforms.

What is most valuable?

The most valuable feature of Dataiku, in my opinion, is the possibility to use Spark, which is a distributed compute engine. This is a feature that is usually appreciated by our customers. 

Additionally, the automation features have been impactful, particularly in the deployment phase, as we use what Dataiku calls deployer nodes. Dataiku primarily enhances the speed at which our customers can develop or train their machine learning models since it is a drag-and-drop platform. Our clients can easily drag and drop components and use them on the spot.

What needs improvement?

There is room for improvement in terms of allowing for more code-based features. I would love for Dataiku to allow more flexibility with code-based components and provide the possibility to extend it by developing and integrating custom components easily with existing ones.

For how long have I used the solution?

I have been working with Dataiku for about three years.

What's my experience with pricing, setup cost, and licensing?

I find the pricing of Dataiku quite affordable for our customers, as they are usually large companies. However, it is a pricey solution and I primarily recommend it to bigger companies.

Which other solutions did I evaluate?

I researched products like Dataiku, Cloudera, and Databricks.

What other advice do I have?

I would give Dataiku an eight out of ten. Although I generally recommend Dataiku, it is mainly suited for companies that can afford it as it is a pricey solution.

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

Other
Disclosure: My company has a business relationship with this vendor other than being a customer: Reseller
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