Compare IBM SPSS Statistics vs. SAS Visual Data Mining and Machine Learning

IBM SPSS Statistics is ranked 10th in Data Science Platforms with 4 reviews while SAS Visual Data Mining and Machine Learning is ranked 21st in Data Science Platforms. IBM SPSS Statistics is rated 7.8, while SAS Visual Data Mining and Machine Learning is rated 0. The top reviewer of IBM SPSS Statistics writes "Anomaly detection, with a useful algorithm handbook, but it's not scalable". On the other hand, IBM SPSS Statistics is most compared with IBM SPSS Modeler, Weka and MathWorks Matlab, whereas SAS Visual Data Mining and Machine Learning is most compared with SAS Enterprise Miner, IBM Watson Studio and H2O.ai.
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Most Helpful Review
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Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: November 2019.
383,162 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:

Pricing and Cost Advice
We think that IBM SPSS is expensive for this function.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.

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Ranking
10th
Views
3,443
Comparisons
2,839
Reviews
3
Average Words per Review
429
Avg. Rating
8.0
21st
Views
614
Comparisons
490
Reviews
0
Average Words per Review
0
Avg. Rating
N/A
Top Comparisons
Compared 11% of the time.
Also Known As
SPSS StatisticsVisual Data Mining and Machine Learning
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IBM
SAS
Overview
Your organization has more data than ever, but spreadsheets and basic statistical analysis tools limit its usefulness. IBM SPSS Statistics software can help you find new relationships in the data and predict what will likely happen next. Virtually eliminate time-consuming data prep; and quickly create, manipulate and distribute insights for decision making.

SAS Visual Data Mining and Machine Learning combines data wrangling, data exploration, visualization, feature engineering, and modern statistical, data mining and machine learning techniques all in a single, scalable in-memory processing environment. This provides faster, more accurate answers to complex business problems, increased deployment flexibility and one easy-to-administer and fluid IT environment.

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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
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Find out what your peers are saying about Alteryx, Knime, IBM and others in Data Science Platforms. Updated: November 2019.
383,162 professionals have used our research since 2012.
We monitor all Data Science Platforms 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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