Compare IBM SPSS Modeler vs. Teradata Analytics

IBM SPSS Modeler is ranked 1st in Data Mining with 21 reviews while Teradata Analytics is ranked 28th in Business Intelligence (BI) Tools with 2 reviews. IBM SPSS Modeler is rated 8.0, while Teradata Analytics is rated 7.0. The top reviewer of IBM SPSS Modeler writes "Ease of use, the user interface, is the best part; the ability to customize streams with R and Python is useful". On the other hand, the top reviewer of Teradata Analytics writes "Streamlines formulating solutions based on SQL-like queries". IBM SPSS Modeler is most compared with KNIME, Alteryx and IBM Watson Studio, whereas Teradata Analytics is most compared with Teradata Vantage, KNIME and SAS Enterprise Miner.
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Most Helpful Review
Find out what your peers are saying about IBM, Knime, SAS and others in Data Mining. Updated: October 2019.
371,639 professionals have used our research since 2012.
Quotes From Members

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

Pros
Automated modelling, classification, or clustering are very useful.A lot of jobs that are stuck in Excel due to the huge numbers of rows are tackled pretty quickly.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.It makes pretty good use of memory. There are algorithms take a long time to run in R, and somehow they run more efficiently in Modeler.New algorithms are added into every version of Modeler, e.g., SMOTE, random forest, etc. The Derive node is used for the syntax code to derive the data.We use analytics with the visual modeling capability to leverage productivity improvements.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 itThe ease of use in the user interface is the best part of it. The ability to customize some of my streams with R and Python has been very useful to me, I've automated a few things with that.

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nPath has made journey/path analysis much easier.It has been fantastic for running complete data sets (no sampling required).Provides ease of formulating a solution based on SQL-like queries.

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Cons
Customer support is hard to contact.It is not integrated with Qlik, Tableau, and Power BI.Expensive to deploy solutions. You need to buy an extra deployment unit.I understand that it takes some time to incorporate some of the new algorithms that have come out in the last few months, in the literature. For example, there is an algorithm based on how ants search for food. And there are some algorithms that have now been developed to complement rules. So that's one of the things that we need to have incorporated into it.The standard package (personal) is not supported for database connection.Unstructured data is not appropriate for SPSS Modeler.Regarding visual modeling, it is not the biggest strength of the product, although from what I hear in the latest release it's going to be a lot stronger. That, to me, has always been the biggest flaw in using this. It's very difficult to get good visualization.I think mapping for geographic data would also be a really great thing to be able to use.

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I would like to see more/better documentation. They also need to enhance analytic/data science algorithms.We have struggled with uptime. Some of the features need to be updated.I have found some problems with the figures depicted on graphs and figures shown, like scores which could not be negative but which were depicted as such.

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Pricing and Cost Advice
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.It got us a good amount of money with quick and efficient modeling.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 a huge increase to time savings.If you are in a university and the license is free then you can use the tool without any charges, which is good.

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Ranking
1st
out of 16 in Data Mining
Views
9,617
Comparisons
7,341
Reviews
22
Average Words per Review
452
Avg. Rating
8.0
Views
850
Comparisons
643
Reviews
2
Average Words per Review
248
Avg. Rating
7.0
Top Comparisons
Compared 18% of the time.
Compared 14% of the time.
Compared 10% of the time.
Also Known As
SPSS ModelerTeradata Aster Analytics, Aster Analytics
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IBM
Teradata
Overview

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.

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


Teradata Aster® Analytics Portfolio provides a suite of ready-to-use, multi-genre advanced analytics functions that empowers business users to uncover and operationalize non-intuitive insights. Teradata Aster Analytics includes the Aster Database, Aster Client and the Aster Portfolio that consists of SQL, SQL-MapReduce and Graph functions for multi-genre advanced analytics. These functions provide everything from data acquisition and preparation to analytic modeling and visualization.

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Sample Customers
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
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Top Industries
REVIEWERS
Financial Services Firm25%
Manufacturing Company15%
Healthcare Company10%
Government10%
VISITORS READING REVIEWS
Software R&D Company21%
Financial Services Firm13%
Government10%
Comms Service Provider9%
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Find out what your peers are saying about IBM, Knime, SAS and others in Data Mining. Updated: October 2019.
371,639 professionals have used our research since 2012.
We monitor all Data Mining reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
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