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Dataiku vs SAP Predictive Analytics [EOL] comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Apr 15, 2026

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
Average Rating
8.2
Reviews Sentiment
6.5
Number of Reviews
21
Ranking in other categories
Data Science Platforms (2nd)
SAP Predictive Analytics [EOL]
Average Rating
8.6
Reviews Sentiment
7.1
Number of Reviews
3
Ranking in other categories
No ranking in other categories
 

Featured Reviews

SK
Senior Data Scientist at Deloitte
Visual workflows have streamlined healthcare analytics and have reduced reporting time significantly
In terms of improvement, I cannot comment on the LLMs or the agentic view as I have not used them yet. However, I feel that better documentation is necessary. Dataiku should establish a stronger community since this is proprietary software, where users can share knowledge. Although they have some community interaction, it is often challenging to find assistance when stuck. For example, when I was new to Dataiku and trying to use an external optimization tool such as CPLEX, I struggled with resource directory linking to a project's notebook. Detailed documentation and community discussions could have significantly alleviated these issues for users such as myself.
Gary Cook - PeerSpot reviewer
Executive at Empowered Analytics
Enables us to forecast and pull trends and has an easy installation
My rating for SAP Predictive Analytics would be an eight out of ten. If I have to be bold, I'll probably say that we're building away hours, and we are actually putting a lot of the actual predicting stuff back into the warehouse. So running it very bi-directionally. So I'm not sure what its integration features are at the moment, but that's an area we're going to look into in the next month or so.

Quotes from Members

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

Pros

"Traceability is vital since I manage many cohorts, and collaboration is key as I have multiple engineers substituting for one another."
"Using Dataiku has meant that we spend less time on preparing and cleaning data, and we spend less time on blending models together, ultimately meaning that we can spend more time modeling."
"One of the valuable features of Dataiku is the workflow capability."
"The solution is quite stable."
"Dataiku is highly regarded as it is a leader in the Gartner ranking."
"Data Science Studio's data science model is very useful."
"Compared to Informatica, this tool is extremely easy with its GUI-based functionality and large compatibility with various data sources, and maintenance processes are much more automated than ever, with fewer errors."
"Dataiku is a complete platform to build ETL and data pipeline and deploy it, which I appreciate."
"I have found that the solution is very stable."
"The most valuable features are the analytics and reporting."
"SAP Predictive Analytics is better suited for business users because it hides the complexity of the model, whereas Microsoft Azure Machine Learning provides a lot more flexibility for technical professionals to tweak the model."
"We always purchase SAP support because it is very good."
"I think the features of the actual ability to forecast and pull trends and correlations has been really good."
 

Cons

"I have not seen a return on investment with Dataiku in terms of time saved, money saved, or fewer employees needed."
"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."
"We still encounter some integration issues."
"Dataiku is down a lot of times, and we have to wait for sometimes five, ten, or fifteen minutes, after which it gets working again, and during those times, we are unable to get our work done."
"I need to stress upon the part about customer support because there are some product issues we have identified and raised with customer support, but sometimes the response is delayed, so that can be improved."
"However, I feel that better documentation is necessary."
"Maybe on the interface in general, the information can easily get lost."
"The license fee appears to be prohibitively expensive and overly secretive, leading our clients to opt for cloud-based solutions that only charge for data storage and processing time."
"This solution works for acquired data but not live, real-time data."
 

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."
"A free trial version is available for testing out this solution."
"The pricing is reasonable"
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Top Industries

By visitors reading reviews
Financial Services Firm
19%
Manufacturing Company
10%
Computer Software Company
9%
Energy/Utilities Company
5%
Construction Company
19%
Outsourcing Company
10%
Manufacturing Company
7%
Hospitality Company
7%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
By reviewers
Company SizeCount
Small Business6
Midsize Enterprise2
Large Enterprise13
No data available
 

Questions from the Community

What is your experience regarding pricing and costs for Dataiku Data Science Studio?
The licenses are a bit high for companies that are still hesitating to get started with using Dataiku. For my personal projects, I used the thirty-day free trial. Regarding my company, I did not ha...
What needs improvement with Dataiku Data Science Studio?
I have no suggestions for improvements because it's all good; it just sometimes lags a lot, and I don't know if the server is full or what, but it sometimes takes a lot of time while loading and re...
What is your primary use case for Dataiku Data Science Studio?
My main use case for Dataiku involves ETL pipelines, mainly for data analysis, and I majorly use SQL queries for that. For ETL pipelines and data analysis, I had to create the output by combining a...
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Also Known As

Dataiku DSS
SAP BusinessObjects Predictive Analytics, BusinessObjects Predictive Analytics, BOPA
 

Overview

 

Sample Customers

BGL BNP Paribas, Dentsu Aegis, Link Mobility Group, AramisAuto
mBank
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