IBM SPSS Modeler vs. SAS Viya

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
IBM SPSS Modeler
Score 7.1 out of 10
N/A
IBM SPSS Modeler is a visual data science and machine learning (ML) solution designed to help enterprises accelerate time to value by speeding up operational tasks for data scientists. Organizations can use it for data preparation and discovery, predictive analytics, model management and deployment, and ML to monetize data assets.
$4,670
per year
SAS Viya
Score 6.8 out of 10
N/A
An end-to-end platform for AI, data science, and analytics, used for modeling, as well as management and deployment of AI models.N/A
Pricing
IBM SPSS ModelerSAS Viya
Editions & Modules
IBM SPSS Modeler Personal
4,670
per year
IBM SPSS Modeler Professional
7,000
per year
IBM SPSS Modeler Premium
11,600
per year
IBM SPSS Modeler Gold
contact IBM
per year
No answers on this topic
Offerings
Pricing Offerings
IBM SPSS ModelerSAS Viya
Free Trial
YesYes
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalNo setup fee
Additional DetailsIBM SPSS Modeler Personal enables users to design and build predictive models right from the desktop. IBM SPSS Modeler Professional extends SPSS Modeler Personal with enterprise-scale in-database mining, SQL pushback, collaboration and deployment, champion/challenger, A/B testing, and more. IBM SPSS Modeler Premium extends SPSS Modeler Professional by including unstructured data analysis with integrated, natural language text and entity and social network analytics. IBM SPSS Modeler Gold extends SPSS Modeler Premium with the ability to build and deploy predictive models directly into the business process to aid in decision making. This is achieved with Decision Management which combines predictive analytics with rules, scoring, and optimization to deliver recommended actions at the point of impact.
More Pricing Information
Community Pulse
IBM SPSS ModelerSAS Viya
Features
IBM SPSS ModelerSAS Viya
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
IBM SPSS Modeler
7.0
Ratings
18% below category average
SAS Viya
-
Ratings
Connect to Multiple Data Sources7.00 Ratings00 Ratings
Extend Existing Data Sources7.00 Ratings00 Ratings
User Ratings
IBM SPSS ModelerSAS Viya
Likelihood to Recommend
7.0
(0 ratings)
8.0
(0 ratings)
Likelihood to Renew
-
(0 ratings)
4.5
(0 ratings)
Usability
8.0
(0 ratings)
6.1
(0 ratings)
Availability
-
(0 ratings)
10.0
(0 ratings)
Performance
-
(0 ratings)
9.0
(0 ratings)
Support Rating
10.0
(0 ratings)
10.0
(0 ratings)
In-Person Training
-
(0 ratings)
9.0
(0 ratings)
Online Training
-
(0 ratings)
8.0
(0 ratings)
Implementation Rating
-
(0 ratings)
9.0
(0 ratings)
Configurability
-
(0 ratings)
10.0
(0 ratings)
Ease of integration
-
(0 ratings)
8.0
(0 ratings)
Product Scalability
-
(0 ratings)
9.0
(0 ratings)
Vendor post-sale
-
(0 ratings)
10.0
(0 ratings)
Vendor pre-sale
-
(0 ratings)
10.0
(0 ratings)
User Testimonials
IBM SPSS ModelerSAS Viya
Likelihood to Recommend
Modeler is well suited for understanding consumer data. The ability to create a prediction and then to understand what is driving that prediction is strong in Modeler. Modeler is closely aligned with the CRISP-DM data mining approach meaning it is not just the 'doing' but also the theoretical background behind the development of data mining models.
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We piloted SAS AA at my organization to see how well it compares with other free software tools such as RStudio and Anaconda. So far what we saw was very impressive especially with the visual display but was a little out of our price range. It would be useful in analyzing population health metrics combined with financial data.
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Pros
  • A very nice and easy to use interface.
  • A great variety of analytics, from statistical calculation to data validation and predictive statistics.
  • Has a steep learning curve.
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  • SAS is can be used as query builder tool which can automate a lot of excel process.
  • There are variety of statistical options available that tie up good visual analytics.
  • There are inbuilt models available for different operations which doesn't require any coding and are easy to run.
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Cons
  • Some Analyses aren't there out of the box but can be added through open languages like R and Python.
  • Graphs could be better.
  • Unable to read data stored in OLAP databases
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  • SAS Analytics does not have very good graphic capabilities. Their advanced graphics packages are expensive, and still not very appealing or intuitive to customize.
  • SAS Analytics is not as up-to-date when it comes to advanced analytical techniques as R or other open-source analytics packages.
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Likelihood to Renew
No answers on this topic
Not only does SAS become easier to use as the user gets more familiar with its capabilities, but the customer service is excellent. Any issues with SAS and their technical team is either contacting the user via email, chat, text, WebEx, or phone. They have power users that have years of experience with SAS there to help with any issue.
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Usability
The ability to do predictive modeling, text analytics for both structured & unstructured data, decision management, optimization, and support for various data sources
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If SAS Enterprise Guide is utilized any beginning user will be able to shorten the learning curve. This is allow the user a plethora of basic capabilities until they can utilize coding to expand their needs in manipulating and presenting data. SAS is also dedicated to expanding this environment so it is ever growing.
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Reliability and Availability
No answers on this topic
SAS probably has the most market saturation out of all of the analytics software worldwide. They are in every industry and they are knowledgable about every industry. They are always available to take questions, solve issues, and discuss a company's needs. A company that buys SAS software has a dedicated representative that is there for all of their needs.
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Performance
No answers on this topic
Although nothing is perfect, SAS is almost there. The software can handle billions of rows of data without a glitch and runs at a quick pace regardless of what the user wants to perform. SAS products are made to handle data so performance is of their utmost important. The software is created to run things as efficiently as SAS software can to maximize performance.
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Support Rating
The online support board is helpful and the free add ons are incredibly appreciated.
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SAS is generally known for good support that's one of the main reasons to justify the cost of having SAS licenses within our organization is knowing that customer support is just a quick phone call away. I've usually had good experiences with the SAS customer support team it's one of the ways in which the company stands out in my view.
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In-Person Training
No answers on this topic
SAS has regional and national conferences that are dedicated to expanding users' knowledge of the software and showing them what changes and additions they are making to the software. There are user groups in most of the major cities that also provide multi-day seminars that focus on specific topics for education. If online training isn't the best way for the user, there is ample in-person training available.
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Online Training
No answers on this topic
There are online videos, live classes, and resource material which makes training very easy to access. However, nothing is circumstantial so applying your training can get tricky if the user is performing complex tasks. When purchasing software, SAS will also allocate education credits so the user(s) can access classes and material online to help expand their knowledge.
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Implementation Rating
No answers on this topic
Ask as many questions you can before the install to understand the process. Since a third party does the installation your company is sort of a passanger and it is easy to get lost in the process. It also helps to have all users and IT support involved in the install to help increase the knowledge as to how SAS runs and what it needs to perform correctly.
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Alternatives Considered
We additionally use SAS Data Miner as a toolkit. Compared to SAS Data Miner, the SPSS Modeler is a good competitor. SAS probably is more integrated in the market for a visual-based code for data science activities. However, I don't think it offers anything better than SPSS, and I really like several of the helpful components for usability for SPSS like peaks into nodes.
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SAS is faster then both SPSS and STATA. SAS also has better models and graphs when comparing the three softwares. However, STATA and SPSS are more user friendly. It is easy to use SPSS and STATA, because a lot of it is point-click. SAS requires some training to be able to use it as effectively as possible. SAS is better with large data sets, and it is easier to analyze many data points at the same time
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Scalability
No answers on this topic
It all depends on the type of SAS product the user has. Scaleability differs from product to product, and if the user has SAS Office Analytics the scaleability is quite robust. This software will satisfy the majority of the company's analytic needs for years to come. In addition, if SAS is not meeting the users needs the company can easily find SAS solutions that will.
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Return on Investment
  • I am able to study and work from home sustainably
  • I can help others have a high quality university education experience to graduate confident and competent to meet gaps in the wider community
  • Market research for my business
  • Help other small businesses to create viable and high quality products and services
  • Contribute to research projects: ethical, high quality data analyses and interpretation
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  • SAS is pretty expensive, so a company would need to take that into consideration before purchasing a license.
  • A lot of companies are now starting to use SAS Advance Analytics, it is great for sharing data between departments.
  • Presentations come out better when using SAS, and estimates are more precise to the confidence interval.
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ScreenShots

IBM SPSS Modeler Screenshots

Screenshot of Use a single run to test multiple modeling methods, compare results and select which model to deploy. Quickly choose the best performing algorithm based on model performance.Screenshot of Explore geographic data, such as latitude and longitude, postal codes and addresses. Combine it with current and historical data for better insights and predictive accuracy.Screenshot of Capture key concepts, themes, sentiments and trends by analyzing unstructured text data. Uncover insights in web activity, blog content, customer feedback, emails and social media comments.Screenshot of Use R, Python, Spark, Hadoop and other open source technologies to amplify the power of your analytics. Extend and complement these technologies for more advanced analytics while you keep control.