IBM SPSS Modeler vs SAS Visual Analytics comparison

The compared IBM and SAS solutions aren't in the same category. IBM is ranked #4 in DM , with an average rating of 7.0, and holds a 17.3% mindshare in the category. SAS is ranked #9 in DV , with an average rating of 8.5, and holds a 5.2% mindshare. Additionally, 86% of IBM users are willing to recommend the solution, compared to 96% of SAS users who would recommend it.

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Executive Summary

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

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining.

To learn more, read our detailed Data Mining Report (Updated: October 2024).

Buyer's Guide

Data Mining

October 2024

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Categories and Ranking

IBM SPSS Statistics

Mindshare comparison

Data Mining

Data Visualization

Featured Reviews

AbakarAhmat

Software Engineer at a university with 10,001+ employees

Enhancing survey analysis that provides valued insightfulness

I used traditional tools where I would prepare data, click through menus, and use SQL Server for data visualization. We switched to IBM SPSS because it offers strong certification and aligns well with the standards we prioritize in our surveys. In terms of popularity, it stands out as the top choice in the market, especially in the research and university domains. Many different organizations and institutions use SPSS for statistical analytics. While there are other tools like MCLab and similar options available, SPSS is the most renowned and widely used among them.

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PeterHuo

Application Architect at Canada Border Services Agency

Good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the server due to memory leaks. This performance problem bothers people. The performance issue seems to be related to the server. We design streams on the client and submit them to the server, which generates a large SQL statement. There are two potential bottlenecks: one in the server and another in data extraction. I'm unsure about the exact mechanics of data splitting when fetching from the database. When streams become larger, performance bottlenecks may occur in the IBM SPSS Modeler server or the database. Sometimes the server crashes and needs to be restarted to release memory on both sides. I'm not sure exactly where the problem is caused, as I focus on stream design rather than server issues. The problem could be on the IBM SPSS Modeler server and database.

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Robert Heck

Co Owner at Hecht und Heck GmbH

A great solution for big organizations, complex business requirements, and highly sophisticated and specialized statistics

There are a few little things that are predefined and can be done out of the box immediately. There is no business intelligence application that is predefined, which is something some customers or prospects would love to have. Small and mid-sized companies would struggle with it because they prefer something standard that has been predefined by somebody else. For instance the system does not come with a pre-defined accounting, budgeting or planning model for a particular industry. Some competitors come with such a model (e.g. for retail companies) which makes the implementation of course easier if the customer can comproise with this predefined model. SAS does not provide such models but does not demand customers to comply with a foreign business model.

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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

"Most of the product features are good but I particularly like the linear regression analysis."

"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."

"It offers very good visualization."

"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 the user interface because you don't need to write code."

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

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

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

More IBM SPSS Statistics pros

"I was familiar with using IBM SPSS Modeler separately in the private sector before that. It's a good tool for extracting data from data warehouses, creating streams, and manipulating logic to extract final data."

"Automated modelling, classification, or clustering are very useful."

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

"I think the code modeling features are the most valuable and without the need to write a code back with many different possibilities to choose from. And the second one is linked to the activity of the data preparation."

"It’s definitely scalable, it’s all on the same platform, it’s well integrated. I think the integration is important in terms of scalablility because essentially, having the entire suite helps a lot to scale it"

"Extremely easy to use, it offers a generous selection of proprietary machine learning algorithms."

"It helped me in that I didn't need to write them by hand, and I could get a result in one or two minutes. That helped me a lot."

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

More IBM SPSS Modeler pros

"We've found the product to be stable and reliable."

"I like SAS Visual Analytics for its ability to provide an initial understanding of data through exploration, even before deep analytics."

"The alert generation feature also helps in sending out ad hoc messages to the business users if business thresholds have been crossed."

"I use Visual Analytics for enterprise reporting."

"The visualization capabilities and the email functionality are most beneficial."

"The speed to display charts and react to users' choices is great."

"Quick deployment to dashboards and analytics features (using SAS Visual Statistics and Enterprise Guide). Easy to create a simple forecast and discover business insights using segmentation tools."

"Simplifies report designs and quickly displays tables and graphs."

More SAS Visual Analytics pros

Cons

"Needs more statistical modelling functions."

"The product should provide more ways to import data and export results that are user-friendly for high-level executives."

"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."

"The technical support should be improved."

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

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

"I know that SPSS is a statistical tool but it should also include a little bit of analytical behavior. You can call it augmented analysis or predictive analysis. The bottom line is it should have more graphical and analytical capabilities."

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

More IBM SPSS Statistics cons

"The integration with sources and visualisation needs some improvement. The scalability needs improvement."

"It is very good, but slow. The slowness may be because we have not finalized all the background information in SPSS. It still needs some tweaking."

"The forecasting could be a bit easier."

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

"We have run into a few problems doing some entity matching/analytics."

"The product does not have a search function for tags."

"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."

"Requires more development."

More IBM SPSS Modeler cons

"It is not as mature as competitors such as Tableau and QlikView."

"Colours used on report objects"

"The reason we haven't rolled it out across the board is due to the fact that the licensing is so expensive."

"There is room for improvement in anti-money laundering prevention and operation monitoring, as well as operation monitoring surveillance."

"There are certain shortcomings in the tool's support services, making it an area where improvements are required."

"There are scalability issues. It depends on the data volume and number of end-users. VA requires a lot of hardware resources to move volumes of data."

"The visualization should be better in SAS Visual Analytics. It is easy to use but when compared to other solutions it is lacking and the support is not very good."

"The deployment isn't smooth. Deploying Visual Analytics on the cloud takes a lot of work, or you can use some providers that give you SAS as a service. For example, there is a provider called SaasNow. They host SAS Visual Analytics and the license. You can buy the license and deploy it there without the hassle of installation because deploying the software isn't easy."

More SAS Visual Analytics cons

Pricing and Cost Advice

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

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

"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."

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

"The price of IBM SPSS Statistics could improve."

"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."

More IBM SPSS Statistics pricing and cost advice

"$5,000 annually."

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

"This tool, being an IBM product, is pretty expensive."

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

"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."

"The scalability was kind of limited by our ability to get other people licenses, and that was usually more of a financial constraint. It's expensive, but it's a good tool."

"It is an expensive product."

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

More IBM SPSS Modeler pricing and cost advice

"Licensing is simple."

"It's approximately $114,000 US dollars per year."

"The product is quite expensive."

"$10,000 per annum for an enterprise license."

"The cost of the solution can be expensive. There is an additional cost for users."

"It was licensed for corporate use, and its licensing was on a yearly basis."

"I work with the tool's free version...The tool's corporate version is very expensive and requires a monthly hire."

"Visual Analytics is expensive for a small company like mine. You also need to deploy it on a server or cloud, so you pay for the license as well as the cost of the cloud or the server that you will deploy on."

More SAS Visual Analytics pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

University

Computer Software Company

Manufacturing Company

Educational Organization

13%

Financial Services Firm

13%

Computer Software Company

University

Financial Services Firm

20%

Government

13%

Computer Software Company

10%

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?

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 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?

The government has funds and a budget, it's hard to say if it's expensive or cheap. In Canada, they have a yearly bud...

See all answers

What needs improvement with IBM SPSS Modeler?

There are performance issues. Extracting data from many combined tables can take hours and occasionally crash the ser...

See all answers

What do you like most about SAS Visual Analytics?

The most solution's notable aspect, in my view, is the ability to integrate various data sources and harness advanced...

See all answers

What is your experience regarding pricing and costs for SAS Visual Analytics?

It's about an average of five. It's easy to scale, but it comes with cost.

See all answers

What needs improvement with SAS Visual Analytics?

Some capabilities are missing compared to Power BI, especially when working with spreadsheet types. Furthermore, Exce...

See all answers

Comparisons

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Weka vs IBM SPSS Statistics

Compared 11% of the time

Oracle Advanced Analytics vs IBM SPSS Statistics

Compared 7% of the time

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Microsoft Power BI vs IBM SPSS Modeler

Compared 28% of the time

KNIME vs IBM SPSS Modeler

Compared 15% of the time

RapidMiner vs IBM SPSS Modeler

Compared 8% of the time

Alteryx vs IBM SPSS Modeler

Compared 7% of the time

Dataiku vs IBM SPSS Modeler

Compared 3% of the time

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Tableau vs SAS Visual Analytics

Compared 25% of the time

Microsoft Power BI vs SAS Visual Analytics

Compared 21% of the time

Databricks vs SAS Visual Analytics

Compared 13% of the time

Microsoft Azure Machine Learning Studio vs SAS Visual Analytics

Compared 5% of the time

Apache Superset vs SAS Visual Analytics

Compared 2% of the time

More SAS Visual Analytics Competitors

Product Reports

Buyer's Guide

IBM SPSS Statistics

November 2024

Download IBM SPSS Statistics product report

Buyer's Guide

IBM SPSS Modeler

November 2024

Download IBM SPSS Modeler product report

Buyer's Guide

SAS Visual Analytics

October 2024

Download SAS Visual Analytics product report

Also Known As

SPSS Statistics

SPSS Modeler

SAS BI

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IBM

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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.”

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

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https://www.ibm.com/account/reg/us-en/signup?formid=urx-19947

SAS Visual Analytics is a data visualization tool that is used for reporting, data exploration, and analytics. The solution enables users - even those without advanced analytical skills - to understand and examine patterns, trends, and relationships in data. SAS Visual Analytics makes it easy to create and share reports and dashboards that monitor business performance. By using the solution, users can handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. SAS Visual Analytics is most suitable for larger companies with complex needs.

SAS Visual Analytics Features

SAS Visual Analytics has many valuable key features. Some of the most useful ones include:

Data
Interactive data discovery
Augmented analytics
Chat-enabled analytics
Sharing and collaboration
Visual analytics apps
Embedded insights
Location analytics
Security and administration
In-memory engine

SAS Visual Analytics Benefits

There are many benefits to implementing SAS Visual Analytics. Some of the biggest advantages the solution offers include:

Machine learning and natural language: SAS Visual Analytics uses machine learning and natural language explanations to find, visualize, and narrate stories and insights that are easy to understand and explain. This enables you to find out why something happened, examine all options, and uncover opportunities hidden deep in your data.

Easy and efficient reporting: With SAS Visual Analytics, you can create interactive reports and dashboards so you can quickly summarize key performance metrics and share them via the web and mobile devices.

Easy to use: SAS Visual Analytics was designed to be easy to use. Its easy-to-use predictive analytics enables even business analysts to assess possible outcomes, which also helps organizations make smarter, data-driven decisions.

Self-service data: Self-service data preparation gives users the ability to import their own data, join tables, create calculated columns, apply data quality functions, and more. In turn, the solution empowers users to access, combine, clean, and prepare their own data in an agile way, which helps facilitate faster, broader adoption of analytics for your entire organization.

Reviews from Real Users

Below are some reviews and helpful feedback written by PeerSpot users currently using the SAS Visual Analytics solution.

A Senior Manager at a consultancy says, “The solution is very stable. The scalability is good. The usability is quite good. It's quite easy to learn and to progress with SAS from an end-user perspective.

PeerSpot user Robert H., Co-owner at Hecht und Heck GmbH, comments, “What I really love about the software is that I have never struggled in implementing it for complex business requirements. It is good for highly sophisticated and specialized statistics in the areas that some people tend to call artificial intelligence. It is used for everything that involves visual presentation and analysis of highly sophisticated statistics for forecasting and other purposes.

Andrea D., Chief Technical Officer at Value Partners, explains, “The best feature is that SAS is not a single BI tool. Rather, it is part of an ecosystem of tools, such as tools that help a user to develop artificial intelligence, algorithms, and so on. SAS is an ecosystem. It's an ecosystem of products. We've found the product to be stable and reliable. The scalability is good.”

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

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

Staples, Ausgrid, Scotiabank, the Australian Institute of Health and Welfare, the Blue Cross and Blue Shield of North Carolina, Oklahoma Gas & Electric, Xcel Energy, and Triad Analytics Solutions.

Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining. Updated: October 2024.

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