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Dataiku vs IBM Watson Studio comparison

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Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

IBM SPSS Statistics
Sponsored
Ranking in Data Science Platforms
10th
Average Rating
8.0
Number of Reviews
37
Ranking in other categories
Data Mining (3rd)
Dataiku
Ranking in Data Science Platforms
7th
Average Rating
8.0
Number of Reviews
8
Ranking in other categories
No ranking in other categories
IBM Watson Studio
Ranking in Data Science Platforms
12th
Average Rating
8.2
Number of Reviews
13
Ranking in other categories
AI Development Platforms (9th)
 

Mindshare comparison

As of November 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.6% compared to the previous year. The mindshare of Dataiku is 11.5%, up from 7.5% compared to the previous year. The mindshare of IBM Watson Studio is 2.1%, down from 2.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

AbakarAhmat - PeerSpot reviewer
Sep 21, 2023
Enhancing survey analysis that provides valued insightfulness
I use it to analyze questionnaire surveys related to a product, solution, or application, such as open data services, which I provide to consumers and end-users. These surveys contain evaluation assessments, and I use SPSS to analyze the responses The most valuable feature is its robust…
Sabrine Bendimerad - PeerSpot reviewer
Jun 11, 2024
Saves a lot of time because I can quickly handle all the data preparation tasks and concentrate on building my machine learning algorithms
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated. While it was theoretically possible to use GitHub with Dataiku, in practice, it was difficult to manage our code effectively and push it from Dataiku to GitHub. Another limitation was its ability to handle different types of data. While Dataiku is powerful for working with structured data, like regular or geospatial data, it struggled with more complex data types such as text and image. In addition to the challenges with GitHub integration, the limited support for diverse data types was another feature lacking at that time.
Abilio Duarte - PeerSpot reviewer
Oct 5, 2023
A highly robust and well-documented platform that simplifies the complex world of AI
It is used to enhance user experience in an e-commerce setting. By leveraging data on user clicks, browsing behavior, and past interactions with the platform, we can create models that enable personalized product recommendations. These models can identify products that align with the customer's…

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."
"Since we are using the software as a statistical tool, I would say the best aspects of it are the regression and segmentation capabilities. That said, I've used it for all sorts of things."
"The most valuable feature is its robust statistical analysis capabilities."
"in terms of the simplicity, I think the SPSS basic can handle it."
"The SPSS interface is very accessible and user-friendly. It's really easy to get information in it. I've shared it with experts and beginners, and everyone can navigate it."
"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."
"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."
"The most valuable features are the small learning curve and its ability to hold a lot of data."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"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 solution is quite stable."
"The most valuable feature is the set of visual data preparation tools."
"Cloud-based process run helps in not keeping the systems on while processes are running."
"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"Data Science Studio's data science model is very useful."
"The advantage is that you can focus on machine learning while having access to what they call 'recipes.' These recipes allow me to preprocess and prepare data without writing any code."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"The system's ability to take a look at data, segment it and then use that data very differently."
"It has a lot of data connectors, which is extremely helpful."
"It is a very stable and reliable solution."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"Watson Studio is very stable."
"It has greatly improved the performance because it is standardized across the company."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
 

Cons

"Improvements are needed in the user interface, particularly in terms of user-friendliness."
"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."
"The design of the experience can be improved."
"Perhaps in terms of visualization. It's not really easy to do some data visualization, just simple, descriptive analysis in SPSS. I think that could be an area for improvement."
"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."
"It could allow adding color to data models to make them easier to interpret."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."
"I find that it is a little slow during use. It takes more time than I would expect for operations to complete."
"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."
"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."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."
"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."
"I think it would help if Data Science Studio added some more features and improved the data model."
"So a better user interface could be very helpful"
"We would like to see it more web-based with more functionality."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"The main challenge lies in visibility and ease of use."
"The decision making in their decision making feature is less good than other options."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"It's sometimes easy to get lost given the number of images the solution opens up when you click on the mouse and the amount of different tabs."
"The solution's interface is very slow at times."
 

Pricing and Cost Advice

"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"The price of IBM SPSS Statistics could improve."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"It's quite expensive, but they do a special deal for universities."
"The price of this solution is a little bit high, which was a problem for my company."
"We think that IBM SPSS is expensive for this function."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"SPSS is an expensive piece of software because it's incredibly complex and has been refined over decades, but I would say it's fairly priced."
"The annual licensing fees are approximately €20 ($22 USD) per key for the basic version and €40 ($44 USD) per key for the version with everything."
"Pricing is pretty steep. Dataiku is also not that cheap."
"IBM Watson Studio is a reasonably priced product"
"The pricing is generally reasonable and straightforward but can vary significantly depending on the specific workloads in use."
"IBM Watson Studio is an expensive solution."
"Watson Studio's pricing is reasonable for what you get."
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Top Industries

By visitors reading reviews
Financial Services Firm
16%
University
10%
Computer Software Company
9%
Manufacturing Company
8%
Financial Services Firm
18%
Educational Organization
16%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
15%
Computer Software Company
13%
Manufacturing Company
9%
University
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about IBM SPSS Statistics?
The software offers consistency across multiple research projects helping us with predictive analytics capabilities.
What is your experience regarding pricing and costs for IBM SPSS Statistics?
While the pricing of the product may be higher, the accompanying service and features justify the investment. However...
What needs improvement with IBM SPSS Statistics?
In some cases, the product takes time to load a large dataset. They could improve this particular area.
What needs improvement with Dataiku Data Science Studio?
One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integratin...
What is your primary use case for Dataiku Data Science Studio?
We use the solution for data science and machine learning.
What needs improvement with IBM Watson Studio?
From an improvement perspective, I would say that if the deployment environment and IBM Watson Studio's environment a...
 

Also Known As

SPSS Statistics
Dataiku DSS
Watson Studio, IBM Data Science Experience, Data Science Experience, DSx
 

Learn More

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Overview

 

Sample Customers

LDB Group, RightShip, Tennessee Highway Patrol, Capgemini Consulting, TEAC Corporation, Ironside, nViso SA, Razorsight, Si.mobil, University Hospitals of Leicester, CROOZ Inc., GFS Fundraising Solutions, Nedbank Ltd., IDS-TILDA
BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
GroupM, Accenture, Fifth Third Bank
Find out what your peers are saying about Dataiku vs. IBM Watson Studio and other solutions. Updated: October 2024.
814,763 professionals have used our research since 2012.