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 #18 with an average rating of 8.5. Dataiku holds a 11.8% 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 SummaryUpdated on Dec 5, 2024

SAS Enterprise Miner and Dataiku compete in the data analytics and machine learning category. Dataiku holds an edge with its collaborative and intuitive workflow capabilities.

Features: SAS Enterprise Miner offers advanced statistical and predictive modeling, integration with SAS code for flexibility, and robust data processing capabilities. Dataiku provides a collaborative platform, visual data preparation tools, and compatibility with multiple data sources.

Room for Improvement: SAS Enterprise Miner could enhance user-friendliness and reduce its technical complexity. It would benefit from quicker deployment processes. Dataiku could improve its scalability for larger enterprise needs and offer deeper customization options. Further enhancement of machine learning algorithm options is also desirable.

Ease of Deployment and Customer Service: SAS Enterprise Miner has a steeper learning curve, often leading to longer deployment times but offers excellent technical support. Dataiku facilitates smoother deployment with a focus on user-friendly interfaces and provides comprehensive support and resources for seamless assistance.

Pricing and ROI: SAS Enterprise Miner generally requires a higher initial investment with training and implementation costs, affecting short-term ROI. Dataiku offers flexible pricing and is seen as providing better ROI due to lower setup costs and faster deployment, appealing to businesses seeking quick returns.

To learn more, read our detailed Dataiku vs. SAS Enterprise Miner Report (Updated: December 2024).

Buyer's Guide

Dataiku vs. SAS Enterprise Miner

December 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

As of December 2024, in the Data Science Platforms category, the mindshare of IBM SPSS Statistics is 2.7%, up from 2.7% compared to the previous year. The mindshare of Dataiku is 11.8%, up from 7.6% 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

Md Masudul Hassan

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

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

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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Shilpa Prakash

Analytics Lead at Pegasus

Good stability, very good data analysis tool pack and excellent documentation

The solution should be faster. Virtualization could be much better. The solution could add some freeware. The text analytics, for example, aren't there in the VSL version. It requires a separate license. It should be included in the main solution's license as it's a basic requirement. It's shouldn't cost extra.

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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

"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 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."

"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."

"The most valuable features are the small learning curve and its ability to hold a lot of data."

"The most valuable features are the solution is easy to use, training new users is not difficult, and our usage is comprehensive because the whole service is beneficial."

"It is perfectly adequate if all you need are the results and not the trail of evidence."

"in terms of the simplicity, I think the SPSS basic can handle it."

"The software offers consistency across multiple research projects helping us with predictive analytics capabilities."

More IBM SPSS Statistics pros

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

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

"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."

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

"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

"The most valuable feature is the decision tree creation."

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

"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."

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

"The technical support is very good."

"The solution is very good for data mining or any mining issues."

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

"he solution is scalable."

More SAS Enterprise Miner pros

Cons

"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."

"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."

"The solution could improve by providing a visual network for predictions and a self-organizing map for clustering."

"In some cases, the product takes time to load a large dataset. They could improve this particular area."

"Most of the package will give you the fixed value, or the p-value, without an explanation as to whether it it significant or not. Some beginners might need not just the results, but also some explanation for them."

"I would like SPSS to improve its integration with other data-filing IBM tools. I also think its duration with data, utilization, and graphics could be better."

"There is a learning curve; it's not very steep, but there is one."

"SPSS is a tool that's been around since the late 60s, and it's the universal worldwide standard for quantitative social science data analysis. That said, it does seem a bit strange to me that the graphical output functions are so clunky after all these years. The output of charts and graphs that SPSS produces is hideous."

More IBM SPSS Statistics cons

"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."

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

"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."

"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."

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

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

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

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

More Dataiku cons

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

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

"Virtualization could be much better."

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

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

"Technical support could be improved."

"The ease of use can be improved. When you are new it seems a bit complex."

"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."

More SAS Enterprise Miner cons

Pricing and Cost Advice

"I rate the tool's pricing a five out of ten."

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

"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."

"We think that IBM SPSS is expensive for this function."

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

"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."

"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."

"The solution must improve its licensing models."

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Computer Software Company

University

Manufacturing Company

Financial Services Firm

18%

Educational Organization

16%

Manufacturing Company

Computer Software Company

Financial Services Firm

25%

University

13%

Educational Organization

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?

The cost of IBM SPSS Statistics is managed by organizations, not individual researchers. It is a very expensive produ...

See all answers

What needs improvement with IBM SPSS Statistics?

IBM SPSS Statistics does not keep you close to your data like KNIME. In KNIME, at every stage, you can see the result...

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

IBM SPSS Modeler vs IBM SPSS Statistics

Compared 16% of the time

Alteryx vs IBM SPSS Statistics

Compared 13% of the time

TIBCO Statistica vs IBM SPSS Statistics

Compared 12% of the time

Microsoft Azure Machine Learning Studio vs IBM SPSS Statistics

Compared 12% of the time

KNIME vs IBM SPSS Statistics

Compared 3% of the time

More IBM SPSS Statistics Competitors

Databricks vs Dataiku

Compared 37% of the time

KNIME vs Dataiku

Compared 15% 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 38% of the time

IBM SPSS Modeler vs SAS Enterprise Miner

Compared 23% of the time

KNIME vs SAS Enterprise Miner

Compared 15% of the time

RapidMiner vs SAS Enterprise Miner

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs SAS Enterprise Miner

Compared 11% of the time

More SAS Enterprise Miner Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

December 2024

Download IBM SPSS Statistics product report

Buyer's Guide

Dataiku

December 2024

Download Dataiku product report

Buyer's Guide

Data Mining

November 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

December 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: December 2024.

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