Dataiku vs SAS Enterprise Miner comparison

Dataiku and SAS are both solutions in the Data Science Platforms category. Dataiku is ranked #7 with an average rating of 7.5, while SAS is ranked #17 with an average rating of 8.5. Dataiku holds a 11.5% mindshare in Data Science Platforms, compared to SAS’s 0.7% mindshare. Additionally, 100% of Dataiku users are willing to recommend the solution, compared to 93% of SAS users who would recommend it.

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Dataiku and SAS Enterprise Miner 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. SAS Enterprise Miner Report (Updated: October 2024).

Buyer's Guide

Dataiku vs. SAS Enterprise Miner

October 2024

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Categories and Ranking

IBM SPSS Statistics

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 SAS Enterprise Miner is 0.7%, down from 1.0% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Science Platforms

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

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…

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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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reviewer1352853

Executive Head of analytics at a retailer with 5,001-10,000 employees

Aug 25, 2023

A stable product that is easy to deploy and can be used for structured and unstructured data mining

We use the solution for predictive analytics to do structured and unstructured data mining I like the way the product visually shows the data pipeline. The product must provide better integration with cloud-native technologies. I have been using the solution for 20 years. The product is very…

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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

"It has helped our analyst unit deliver work with more transparency and confidence, given that we can always view the dataset in totality, after each step of data transformation."

"Some of the most valuable features that we are using with some business models are machine learning algorithms, statistical models given to us by the business, and getting data from the database or text files."

"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."

"Capability analysis is one of the main and valuable functions. We also do some hypothesis testing in Minitab and summary stats. These are the functions that we find very useful."

"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 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."

"In terms of the features I've found most valuable, I'd say the duration, the correlation, and of course the nonparametric statistics. I use it for reliability and survival analysis, time series, regression models in different solutions, and different types of solutions."

"It has the ability to easily change any variable in our research."

More IBM SPSS Statistics pros

"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."

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

"Data Science Studio's data science model is very useful."

"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."

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

More Dataiku pros

"The setup is straightforward. Deployment doesn't take more than 30 minutes."

"The most valuable feature is that you can use multiple algorithms for creating models and then you can compare the results between them."

"The technical support is very good."

"I found the ease of use of the solution the most valuable. Additionally, other valuable features include: the user interface, power to extract data, compatibility with other technologies (specifically with PS400), and automation of several tasks."

"he solution is scalable."

"Most of the features, especially on the data analysis tool pack, are really good. The way they do clustering and output is great. You can do fairly elaborate outputs. The results, the ensembles, all of these, are fantastic."

"Good data management and analytics."

"The solution is able to handle quite large amounts of data beautifully."

More SAS Enterprise Miner pros

Cons

"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 design of the experience can be improved."

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

"SPSS slows down the computer or the laptop if the data is huge; then you need a faster computer."

"The technical support should be improved."

"It could provide even more in the way of automation as there are many opportunities."

"Needs more statistical modelling functions."

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

More IBM SPSS Statistics cons

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

"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."

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

"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."

"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."

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

"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

"Technical support could be improved."

"The user interface of the solution needs improvement. It needs to be more visual."

"The solution is very stable, but we do have some problems with discrepancies involving SAS not matching with the latest Java versions. It's not stable in cases where SAS tries to run on a different version because SAS doesn't connect with the latest Java update. Once a month we need to restart systems from scratch."

"While I don't personally need tutorials, I can't say that it wouldn't be helpful for others to have some to help them navigate and operate the system."

"The solution needs an easier interface for the user. The user experience isn't so easy for our clients."

"The initial setup is challenging if doing it for the first time."

"The visualization of the models is not very attractive, so the graphics should be improved."

"The product must provide better integration with cloud-native technologies."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"The price of this solution is a little bit high, which was a problem for my company."

"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."

"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."

"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."

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

More IBM SPSS Statistics pricing and cost advice

"Pricing is pretty steep. Dataiku is also not that cheap."

"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."

"The solution must improve its licensing models."

"This solution is for large corporations because not everybody can afford it."

"The solution is expensive for an individual, but for an enterprise/institution (purchasing bulk licenses), it is not a high price for the use that will come from it."

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Top Industries

By visitors reading reviews

Financial Services Firm

16%

University

10%

Computer Software Company

Manufacturing Company

Financial Services Firm

18%

Educational Organization

16%

Manufacturing Company

Computer Software Company

Financial Services Firm

25%

University

12%

Educational Organization

11%

Insurance Company

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...

See all answers

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?

It is very expensive.

See all answers

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...

See all answers

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

We use the solution for data science and machine learning.

See all answers

What do you like most about SAS Enterprise Miner?

I like the way the product visually shows the data pipeline.

See all answers

What is your experience regarding pricing and costs for SAS Enterprise Miner?

The solution must improve its licensing models. It bundles all the products into smaller products. We can only have a...

See all answers

What needs improvement with SAS Enterprise Miner?

The product must provide better integration with cloud-native technologies.

See all answers

Comparisons

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IBM SPSS Modeler vs IBM SPSS Statistics

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Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

KNIME vs IBM SPSS Statistics

Compared 3% of the time

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Databricks vs Dataiku

Compared 38% of the time

KNIME vs Dataiku

Compared 14% of the time

Alteryx vs Dataiku

Compared 11% of the time

RapidMiner vs Dataiku

Compared 11% of the time

IBM SPSS Modeler vs Dataiku

Compared 1% of the time

More Dataiku Competitors

SAS Visual Analytics vs SAS Enterprise Miner

Compared 42% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 22% of the time

RapidMiner vs SAS Enterprise Miner

Compared 13% of the time

KNIME vs SAS Enterprise Miner

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner

Compared 12% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

October 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Dataiku

November 2024

Download Dataiku product report

Buyer's Guide

Data Mining

October 2024

Download SAS Enterprise Miner product report

Also Known As

SPSS Statistics

Dataiku DSS

Enterprise Miner

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IBM

Dataiku

SAS

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.

SAS Enterprise Miner is a solution to create accurate predictive and descriptive models on large volumes of data across different sources in the organization. SAS Enterprise Miner offers many features and functionalities for the business analysts to model their data. Some of the business applications are for detecting fraud, minimizing risk, resource demands, reducing asset downtime, campaigns and reduce customer attrition.

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

Generali Hellas, Gitanjali Group, Gloucestershire Constabulary, GS Home Shopping, HealthPartners, IAG New Zealand, iJET, Invacare

Buyer's Guide

Dataiku vs. SAS Enterprise Miner

October 2024

Free Report: Dataiku vs. SAS Enterprise Miner

Find out what your peers are saying about Dataiku vs. SAS Enterprise Miner and other solutions. Updated: October 2024.

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