Dataiku vs IBM SPSS Modeler comparison

Dataiku and IBM are both solutions in the Data Science Platforms category. Dataiku is ranked #7 with an average rating of 8.0, while IBM is ranked #12 with an average rating of 7.0. Dataiku holds a 10.3% mindshare in Data Science Platforms, compared to IBM’s 2.5% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 85% of IBM users who would recommend it.

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Executive Summary

We performed a comparison between Dataiku and IBM SPSS Modeler based on real PeerSpot user reviews.

Find out in this report how the two Data Science Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed Dataiku vs. IBM SPSS Modeler Report (Updated: July 2024).

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

July 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of September 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.8%, up from 2.4% compared to the previous year. The mindshare of Dataiku is 10.3%, up from 7.2% compared to the previous year. The mindshare of IBM SPSS Modeler is 2.5%, down from 2.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

Md Masudul Hassan

Agricultural Finance and IT Researcher at Sher-e-Bangla Agricultural University

Jan 27, 2024

Comprehensive data analysis capabilities with a user-friendly interface, providing an efficient and reliable platform for researchers and analysts

I believe that offering short-term SPSS licenses, perhaps when customer sourcing is available, could make it more affordable. These licenses shouldn't include features tailored for universities or large sales organizations. Instead, they could offer discounts or additional facilities for smaller entities to access the software. In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options. For example, offering basic features to the first hundred users can help them become familiar with the software and its capabilities. This approach encourages users to upgrade to higher tiers as they become more experienced and require additional functionality.

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Sabrine Bendimerad

Data Scientist at Electricite De France

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.

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Abel Georges

Principal Scientist I at a manufacturing company with 10,001+ employees

Jun 8, 2023

An outdated solution that offers stability and requires a straightforward deployment

Mostly, the solution is used for business analytics, including for several CSV files and Oracle databases, in order to sort of create flows for financial reports The solution has not improved the functioning of my company. So, we switched off the solution. In the solution, I like the…

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Quotes from Members

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

Pros

"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 solution is very comprehensive, especially compared to Minitabs, which is considered more for manufacturing. However, whatever data you want to analyze can be handled with SPSS."

"The features that I have found most valuable are the Bayesian statistics and descriptive statistics."

"Custom tables and macros: They allow us to create useful reports quickly for a broad audience."

"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."

"The most valuable features mainly include factor analysis, correlation analysis, and geographic analysis."

"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."

"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."

More IBM SPSS Statistics pros

"The solution is quite stable."

"The most valuable feature is the set of visual data preparation tools."

"If many teams are collaborating and sharing Jupyter notebooks, it's very useful."

"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."

"I like the interface, which is probably my favorite part of the solution. It is really user-friendly for an IT person."

"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."

"Cloud-based process run helps in not keeping the systems on while processes are running."

"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."

More Dataiku pros

"It is very scalable for non-technical people."

"We had an IBM Guardium service contract where we used one of their resources to help us develop our prototype. It was a good experience, but they were helpful and responsive."

"It's very easy to use. The drag and drop feature makes it very easy when you are building and testing the streams. That's very useful."

"IBM was chosen because of usability. It's point and click, whereas the other out-of-the box-solution, or open-source solutions, require full-on programming and a much higher skill level."

"I think it is the point and drag features that are the most valuable. You can simply click at the windows, and then pull up the functions."

"It's a very organized product. It's easy to use."

"It will scale up to anything we need."

"It gives you a GUI interface, which is a lot more user-friendly and easier to use compared to writing R scripts or Python."

More IBM SPSS Modeler pros

Cons

"The design of the experience can be improved."

"The statistics should be more self-explanatory with detailed automated reports."

"This solution is not suitable for use with Big Data."

"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."

"In developing countries, it would be beneficial to provide certain features to users at no cost initially, while also customizing pricing options."

"I'd like to see them use more artificial intelligence. It should be smart enough to do predictions and everything based on what you input."

"Improvements are needed in the user interface, particularly in terms of user-friendliness."

"The solution needs to improve forecasting using time series analysis."

More IBM SPSS Statistics cons

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

"Dataiku still needs some coding, and that could be a difference where business data scientists would go for DataRobot more than Dataiku."

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

"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."

"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."

"I think it would help if Data Science Studio added some more features and improved the data model."

"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."

"One of the main challenges was collaboration. Developers typically use GitHub to push and manage code, but integrating GitHub with Dataiku was complicated."

More Dataiku cons

"Formula writing is not straightforward for an Excel user. Totally new set of functions, which takes time to learn and teach."

"The challenge for the very technical data scientists: It is constraining for them."

"Unstructured data is not appropriate for SPSS Modeler."

"The biggest issue with the visual modeling capability is that we can't extract the SQL code under the hood."

"When you are not using the product, such as during the pandemic where we had worldwide lockdowns, you still have to pay for the licensing."

"If IBM could add some of the popular models into the SPSS for further analysis, like popular regression models, I think that would be a helpful improvement."

"I can say the solution is outdated."

"We would like to see better visualizations and easier integration with Cognos Analytics for reporting."

More IBM SPSS Modeler cons

Pricing and Cost Advice

"It's quite expensive, but they do a special deal for universities."

"The pricing of the modeler is high and can reduce the utility of the product for those who can not afford to adopt it."

"Our licence is on a yearly renewal basis. While pricing is not the primary concern in our evaluation, as products are assessed by whether they can meet our user needs and expertise, the cost can be a limiting factor in the number of licences we procure."

"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 price of IBM SPSS Statistics could improve."

"More affordable training for new staff members."

"While the pricing of the product may be higher, the accompanying service and features justify the investment."

More IBM SPSS Statistics 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."

"If you are in a university and the license is free then you can use the tool without any charges, which is good."

"It got us a good amount of money with quick and efficient modeling."

"Its price is okay for a company, but for personal use, it is considered somewhat expensive."

"Having in mind all four tools from Garner’s top quadrant, the pricing of this tool is competitive and it reflects the quality that it offers."

"$5,000 annually."

"When you are close to end of quarter, IBM and its partners can get you 60% to 70% discounts, so literally wait for the last day of the quarter for the best prices. You may feel like you are getting robbed if you can't receive a good discount."

"I am using the free version of IBM SPSS Modeler, it is the educational edition version."

"It is an expensive product."

More IBM SPSS Modeler pricing and cost advice

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Top Industries

By visitors reading reviews

University

13%

Financial Services Firm

13%

Educational Organization

10%

Computer Software Company

Financial Services Firm

18%

Educational Organization

15%

Manufacturing Company

Computer Software Company

Educational Organization

15%

Financial Services Firm

12%

Computer Software Company

University

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.

See all answers

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...

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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.

See all answers

What is your experience regarding pricing and costs for Dataiku Data Science Studio?

Pricing is pretty steep. Dataiku is also not that cheap. It depends on the client and how much they want to spend tow...

See all answers

What needs improvement with Dataiku Data Science Studio?

The no-code/low-code aspect, where DataRobot doesn't need much coding at all. Dataiku still needs some coding, and th...

See all answers

What is your primary use case for Dataiku Data Science Studio?

My current client has Dataiku. We do sentiment analysis and some small large language models right now. We use Dataik...

See all answers

What do you like most about IBM SPSS Modeler?

Compared to other tools, the product works much easier to analyze data without coding.

See all answers

What is your experience regarding pricing and costs for IBM SPSS Modeler?

It is an expensive product.

See all answers

What needs improvement with IBM SPSS Modeler?

The platform's cloud version needs improvements. The process to access workflow could be user-friendly. It could be e...

See all answers

Comparisons

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Compared 15% of the time

Alteryx vs IBM SPSS Statistics

Compared 15% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

Weka vs IBM SPSS Statistics

Compared 11% of the time

Anaconda vs IBM SPSS Statistics

Compared 3% of the time

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Databricks vs Dataiku

Compared 39% of the time

KNIME vs Dataiku

Compared 14% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 10% of the time

Anaconda vs Dataiku

Compared 1% of the time

More Dataiku Competitors

Microsoft Power BI vs IBM SPSS Modeler

Compared 24% of the time

KNIME vs IBM SPSS Modeler

Compared 21% of the time

RapidMiner vs IBM SPSS Modeler

Compared 9% of the time

Alteryx vs IBM SPSS Modeler

Compared 8% of the time

IBM Watson Studio vs IBM SPSS Modeler

Compared 2% of the time

More IBM SPSS Modeler Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

August 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Dataiku

September 2024

Download Dataiku product report

Buyer's Guide

IBM SPSS Modeler

August 2024

Download IBM SPSS Modeler product report

Also Known As

SPSS Statistics

Dataiku DSS

SPSS Modeler

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IBM

Dataiku

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IBM

Overview

IBM SPSS Statistics is a powerful data mining solution that is designed to aid business leaders in making important business decisions. It is designed so that it can be effectively utilized by organizations across a wide range of fields. SPSS Statistics allows users to leverage machine learning algorithms so that they can mine and analyze data in the most effective way possible.

IBM SPSS Statistics Benefits

Some of the ways that organizations can benefit by choosing to deploy IBM SPSS Statistics include:

Ease of use. SPSS Statistics enables users to simply and intuitively take control of their statistical needs. The solution is designed so that analysts who do not know how to code can easily make full use of the various tools and capabilities that SPSS Statistics has to offer. Its command language is so straightforward that it does not require users to undergo special training before they use it.

Comprehensive and flexible build. SPSS Statistics is designed to be both a comprehensive and highly flexible analytics solution. It enables users to utilize a variety of integrations that make it easy for users to add features that they might feel they are missing.

Automation. SPSS Statistics makes it simple for users to automate basic tasks that they might otherwise devote too much time worrying about. Tasks like calculation or data gathering can be delegated to the system while more conceptual tasks like data analysis are given to an organization’s analysts to handle.

IBM SPSS Statistics Features

Intuitive user interface. SPSS Statistics enables users to deploy an intuitive interface that makes the process of system management simple. Among the other components of this interface is a drag-and-drop feature that makes analysis and management possible for anyone who wants to use it.

Advanced data visualizations. Analysts that employ SPSS Statistics gain access to tools that empower them to create and export data visualizations. These visualizations can be formatted in many different ways depending on what the user needs.

Local data storage. SPSS Statistics has the ability to securely store data on a user’s computer. This enables them to add layers of security that would not necessarily be present if the data was stored in the cloud.

Reviews from Real Users

IBM SPSS Statistics is a highly effective solution that stands out when compared to many of its competitors. Two major advantages it offers are the wealth of functionalities that it provides and its high level of accessibility.

An Emeritus Professor of Health Services Research at a university writes, "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 in a multidimensional setup space. It's the multidimensional space facility that is most useful."

A Director of Systems Management & MIS Operations at a university, says, “The SPSS interface is very accessible and user-friendly. It's really easy to get information from it. I've shared it with experts and beginners, and everyone can navigate it.”

Dataiku Data Science Studio is acclaimed for its versatile capabilities in advanced analytics, data preparation, machine learning, and visualization. It streamlines complex data tasks with an intuitive visual interface, supports multiple languages like Python, R, SQL, and scales efficiently for large dataset handling, boosting organizational efficiency and collaboration.

IBM SPSS Modeler is an extensive predictive analytics platform that is designed to bring predictive intelligence to decisions made by individuals, groups, systems and the enterprise. By providing a range of advanced algorithms and techniques that include text analytics, entity analytics, decision management and optimization, SPSS Modeler can help you consistently make the right decisions from the desktop or within operational systems.

Buy
https://www.ibm.com/products/spss-modeler/pricing

Sign up for the trial
https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

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

Reisebªro Idealtours GmbH, MedeAnalytics, Afni, Israel Electric Corporation, Nedbank Ltd., DigitalGlobe, Vodafone Hungary, Aegon Hungary, Bureau Veritas, Brammer Group, Florida Department of Juvenile Justice, InSites Consulting, Fortis Turkey

Buyer's Guide

Dataiku vs. IBM SPSS Modeler

July 2024

Free Report: Dataiku vs. IBM SPSS Modeler

Find out what your peers are saying about Dataiku vs. IBM SPSS Modeler and other solutions. Updated: July 2024.

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