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Dataiku vs IBM SPSS Statistics comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 5, 2024

Review summaries and opinions

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

Categories and Ranking

Dataiku
Ranking in Data Science Platforms
6th
Average Rating
8.2
Reviews Sentiment
7.1
Number of Reviews
12
Ranking in other categories
No ranking in other categories
IBM SPSS Statistics
Ranking in Data Science Platforms
8th
Average Rating
8.0
Reviews Sentiment
6.9
Number of Reviews
38
Ranking in other categories
Data Mining (3rd)
 

Mindshare comparison

As of April 2025, in the Data Science Platforms category, the mindshare of Dataiku is 12.7%, up from 8.2% compared to the previous year. The mindshare of IBM SPSS Statistics is 2.7%, down from 2.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Science Platforms
 

Featured Reviews

RichardXu - PeerSpot reviewer
The platform organizes workflows visually and efficiently
One of the valuable features of Dataiku is the workflow capability. It allows us to organize a workflow efficiently. The platform has a visual interface, making it much easier for educated professionals to organize their work. This feature is useful because it simplifies tasks and eliminates the need for a data scientist. If you are knowledgeable about AI, you can directly write using primitive tools like Pantera flow, PyTorch, and Scikit-learn. However, Dataiku makes this process much easier.
Laurence Moseley - PeerSpot reviewer
Delivers reliable results for academic research and keeps you close to your data.
SPSS is perfectly adequate if all you want are some results. If you only need the results, you do not require the trail of evidence on how you obtained those results. I mainly used it for cross tabs, correlation, regression, chi-squared tests, and similar analyses often seen in published papers; I used it for my papers as well. For wider uses I find Knime keeps me in touch with my data, however much I transform them.

Quotes from Members

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

Pros

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."
"One of the valuable features of Dataiku is the workflow capability."
"I believe the return on investment looks positive."
"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."
"I rate the overall product as eight out of ten."
"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."
"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 most valuable feature is the set of visual data preparation tools."
"The most valuable feature of IBM SPSS Statistics is all the functionality it provides. Additionally, it is simple to do the five-way analysis that you can into multidimensional setup space. It's the multidimensional space facility that is most useful."
"SPSS can handle whatever you throw at it, whether your data set contains 10,000, 100,000, or a million objects. It's like the heavy artillery of analytical tools."
"I've found the descriptive statistics and cross-tabs valuable. The very simple correlations and regressions are as well."
"They have many existing algorithms that we can use and use effectively to analyze and understand how to put our data to work to improve what we do."
"The most valuable feature is its robust statistical analysis capabilities."
"One feature I found very valuable was the analysis of variance (ANOVA)."
"You can find a complete algorithm in the solution and use it. You don't need to write your own algorithms for predictive analytics. That's the most valuable feature and the main one we use."
"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."
 

Cons

"The license is very expensive. It would be great to have an intermediate license for basic treatments that do not require extensive experience."
"The ability to have charts right from the explorer would be an improvement."
"There is room for improvement in terms of allowing for more code-based features."
"Server up-time needs to be improved. Also, query engines like Spark and Hive need to be more stable."
"One area for improvement is the need for more capabilities similar to those provided by NVIDIA for parallel machine learning training. We still encounter some integration issues."
"Although known for Big Data, the processing time to process 1.8 billion records was terribly slow (five days)."
"The technical support from Dataiku is not good. The support team does not provide adequate assistance, and there are concerns about billing requests."
"I think it would help if Data Science Studio added some more features and improved the data model."
"It would be helpful if there was better documentation on how to properly use the solution. A beginner's guide on how to use the various programming functions within the product would be so useful to a lot of people. I found that everything was very confusing at first. Having clear documentation would help alleviate that."
"If there is any self-generation data collection plan (DCP), it would be helpful in gathering data. It would also be useful if there is a function to scale it up to, let's say, UiPath and have it consolidate and integrate into a UiPath solution."
"The reports could be better."
"One of the areas that should be similar to Minitabs is the use of blogs. The Minitabs blog helps users understand the tools and gives lots of practical examples. Following the SPSS manual is cumbersome. It's a good, exhaustive manual, but it's not practical to use. With Minitabs, you can go to the blogs and find specific articles written about various components and it's very helpful. Without blogs, we find SPSS more complicated."
"The statistics should be more self-explanatory with detailed automated reports."
"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 think the visualization and charting should be changed and made easier and more effective."
"The product should provide more ways to import data and export results that are user-friendly for high-level executives."
 

Pricing and Cost Advice

"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."
"More affordable training for new staff members."
"If it requires lot of data processing, maybe switching to IBM SPSS Clementine would be better for the buyer."
"While the pricing of the product may be higher, the accompanying service and features justify the investment."
"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."
"I rate the tool's pricing a five out of ten."
"The price of this solution is a little bit high, which was a problem for my company."
"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."
"The price of IBM SPSS Statistics could improve."
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Top Industries

By visitors reading reviews
Financial Services Firm
17%
Educational Organization
14%
Manufacturing Company
9%
Computer Software Company
8%
Financial Services Firm
17%
Computer Software Company
9%
University
8%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
The pricing for Dataiku is very high, which is its biggest downside. The model they follow is not consumption-based, making it expensive.
What needs improvement with Dataiku Data Science Studio?
Dataiku's pricing is very high, and commercial transparency is a challenge. Support is also an area needing improvement. More features like LLM security, holographic encryption, and enhanced GPU in...
What is your primary use case for Dataiku Data Science Studio?
My primary use case for Dataiku ( /products/dataiku-reviews ) is for data science, Gen ( /products/gen-reviews ) AI, and data science applications. Our AGN team also uses it for various purposes.
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?
SPSS is horrendously expensiver. On a laptop Knime is free of charge (Windows, Mac, Linux)
What needs improvement with IBM SPSS Statistics?
Better guidance both in producing programs and interpreting their output.
 

Comparisons

 

Also Known As

Dataiku DSS
SPSS Statistics
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
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
Find out what your peers are saying about Dataiku vs. IBM SPSS Statistics and other solutions. Updated: March 2025.
845,406 professionals have used our research since 2012.