SAS Visual Analytics vs SAS Visual Data Mining and Machine Learning

SAS Visual Analytics is ranked 2nd in Data Science Platforms with 3 reviews vs SAS Visual Data Mining and Machine Learning which is ranked 18th in Data Science Platforms. The top reviewer of SAS Visual Analytics writes "the best tool for insightful and analytical dashboard development and reporting". SAS Visual Analytics is most compared with Tableau, Microsoft BI and QlikView. SAS Visual Data Mining and Machine Learning is most compared with SAS Enterprise Miner, Microsoft Azure Machine Learning Studio and IBM Data Science Experience.
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Quotes From Members Comparing SAS Visual Analytics vs SAS Visual Data Mining and Machine Learning

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
Pricing and Cost Advice
Licensing is simple.

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Find out what your peers are saying about IBM, SAS, Alteryx and others in Data Science Platforms.
269,925 professionals have used our research since 2012.
Ranking
RANKING
Views
27,304
Comparisons
19,557
Reviews
2
Followers
2,151
Avg. Rating
8.0
Views
401
Comparisons
320
Reviews
0
Followers
27
Avg. Rating
N/A
Top Comparisons
Top Comparisons
Itmwdql1 400x400
Compared 44% of the time.
Microsoft 400x400
Compared 12% of the time.
Qlikview
Compared 9% of the time.
See more SAS Visual Analytics competitors »
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Also Known As
Also Known AsSAS BIVisual Data Mining and Machine Learning
Website/Video
Website/VideoSAS
  • Vendor 7934 screenshot 1526145527
SAS
  • Vendor 7934 screenshot 1526145527
OverviewQuestionmark icon
Overview

SAS Business Intelligence package offers business owners an all-in-one tool for data analysis. It is mainly comprised of analytics software that can handle all of the statistical analysis that a company requires. Functions include mining and managing to fetching important information from a variety of sources and even adapting that information, all for the purpose of analyzing the data for future use.

The SAS Business Intelligence software allows users to handle, understand, and analyze their data in both past and present fields, as well as influence vital factors for future changes. Users can also create and publish reports based on their findings so that others in their field can share the information and input suggestions. The graphic presentation is another benefit that many businesses find useful when presenting their findings to others.

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.

OFFER
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Learn more about SAS Visual Data Mining and Machine Learning
Sample Customers
Sample CustomersStaples, 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.
Information Not Available
Top IndustriesQuestionmark icon
Top Industries
REVIEWERS
Financial Services Firm
20%
Mining And Metals Company
10%
Insurance Company
10%
Government
10%
VISITORS READING REVIEWS
Financial Services Firm
24%
University
9%
Insurance Company
7%
Government
7%
No Data Available
Company SizeQuestionmark icon
Company Size
REVIEWERS
Small Business
25%
Midsize Enterprise
13%
Large Enterprise
63%
VISITORS READING REVIEWS
Small Business
12%
Midsize Enterprise
24%
Large Enterprise
64%
No Data Available
Data science platforms report from it central station 2018 04 21 thumbnail
Find out what your peers are saying about IBM, SAS, Alteryx and others in Data Science Platforms.
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269,925 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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