Predictive Analytics
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SAS Visual Statistics
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Review

SAS Visual Statistics

Overview
Synopsis

SAS Visual Analytics to quickly identify predictive drivers and interactively discover outliers across multiple variables.

Category

Data Analytics Platform

Features

• Visual data exploration and discovery
• Descriptive modeling
• Predictive modeling
• Open, code-based model development
• Dynamic group-by processing
• Model comparison and assessment
• Model scoring
• Distributed, in-memory analytical processing
• Flexible deployment options

License

Proprietary

Price

Contact for Pricing

Pricing

Subscription

Free Trial

Available

Users Size

Small (<50 employees), Medium (50 to 1000 employees), Enterprise (>1001 employees)

Company

SAS

URL

https://www.sas.com

What is best?

• Visual data exploration and discovery
• Descriptive modeling
• Predictive modeling
• Open, code-based model development
• Dynamic group-by processing
• Model comparison and assessment
• Model scoring

What are the benefits?

• Most appropriate analytical modeling
• Easily build and refine models
• Empower multiple users to interact
• Flexible deployment options
• Code-based model development

PAT Rating™
Editor Rating
Aggregated User Rating
Rate Here
Ease of use
7.6
8.3
Features & Functionality
7.8
8.1
Advanced Features
7.8
8.5
Integration
7.7
8.6
Performance
7.7
7.6
Customer Support
7.6
8.6
Implementation
8.4
Renew & Recommend
7.8
Bottom Line

Visually explore and evaluate segments for further analysis using k-means clustering, scatter plots and detailed summary statistics

7.7
Editor Rating
8.3
Aggregated User Rating
1 rating
You have rated this

SAS Visual Analytics to quickly identify predictive drivers and interactively discover outliers across multiple variables. Then create powerful descriptive and predictive models with a simple drag-and-drop interface.

Visually explore and evaluate segments for further analysis using k-means clustering, scatter plots and detailed summary statistics. Build predictive models using a variety of techniques – linear regression, generalized linear modeling, logistic regression, classification trees.

Design and distribute BI reports and dashboards. Explore relevant data through interactive data discovery. And provide easy-to-use, self-service analytics to more users.

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1 Reviews
  • Kimberly Tovey
    June 21, 2017 at 12:16 pm

    Integration with external software

    What is best?

    A great and very useful capability of SAS Visual Statistics is SAS Viya in-memory capabilities, which allows to perform processing in memory and distribute processing across nodes in a cluster. This process held in memory workload as long as required, across jobs and user boundaries, reducing latency.

    Company size

    Medium (50 to 1000)

    User Role

    Super User

    User Industry

    Financial services

    Rating
    Ease of use8.3

    Features & Functionality8.1

    It offers a variety of data explorations via visual analysis, such as linear regression, predictive outputs and segmentation, offers modelling visualisation tasks, allows drawing bar charts, histograms, box plots, heat maps, bubble plots, geographic maps and more, detect outliers or filter observations.

    Advanced Features8.5

    Integration8.6

    SAS Visual Statistics also offers integration with a variety of others external software like Python, R, Lua, Java, Pandas, matplotlib, Plotly, Bokeh, and others. Both analytical and descriptive techniques are enhanced with SAS® Visual Statistics, but also group processing, models comparisons, assessments and scoring.

    Performance7.6

    Training 8.4

    Customer Support8.6

    Implementation8.4

    Renew & Recommend7.8

    ADDITIONAL INFORMATION
    SAS Visual Statistics is a powerful software that allows data visualization in order to improve findings from data scientists and statisticians and enhance your previsions and data analytical skills in your business.

Ease of use
Features & Functionality
Advanced Features
Integration
Performance
Customer Support
Implementation
Renew & Recommend

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