TrustRadius

Altair SLC vs. Design-Expert

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Altair SLC
Score 9.2 out of 10
N/A
Altair SLC (formerly the WPS industrial analytics platform, acquired by Altair in late 2021) is designed for data science and heavyweight data processing with the languages of SAS and R. Best known for its SAS language compiler, the software includes advanced graphical user interfaces, robust, high-performance data processing and production-ready application frameworks.N/A
Design-Expert
Score 0.0 out of 10
N/A
Design-Expert from Stat-Ease includes tools to lay out an ideal experiment on process, mixture or combination of factors and components, featuring in-line power calculations and the ability to add blocks and center points. Design-Expert’s design wizards and layouts such as the stoplight configuration for two-level factorials make it easier to design experiments.
$1,035
per year
Pricing
Altair SLCDesign-Expert
Editions & Modules
No answers on this topic
Subscription
$1035
per year
Standard Network
$1860+
per year on-premise floating license
Buy Once
$2950
one-time fee
Offerings
Pricing Offerings
Altair SLCDesign-Expert
Free Trial
YesNo
Free/Freemium Version
YesNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeOptionalNo setup fee
Additional Details——
More Pricing Information
Community Pulse
Altair SLCDesign-Expert
Features
Altair SLCDesign-Expert
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
Altair SLC
8.6
Ratings
2% above category average
Design-Expert
-
Ratings
Customizable dashboards8.60 Ratings00 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
Altair SLC
8.6
Ratings
8% above category average
Design-Expert
-
Ratings
Drill-down analysis8.60 Ratings00 Ratings
Formatting capabilities8.60 Ratings00 Ratings
Integration with R or other statistical packages8.60 Ratings00 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
Altair SLC
8.8
Ratings
4% above category average
Design-Expert
-
Ratings
Publish to Web8.60 Ratings00 Ratings
Publish to PDF8.60 Ratings00 Ratings
Report Delivery Scheduling9.30 Ratings00 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
Altair SLC
9.0
Ratings
10% above category average
Design-Expert
-
Ratings
Pre-built visualization formats (heatmaps, scatter plots etc.)8.60 Ratings00 Ratings
Predictive Analytics9.30 Ratings00 Ratings
User Ratings
Altair SLCDesign-Expert
Likelihood to Recommend
9.2
(0 ratings)
-
(0 ratings)
User Testimonials
Altair SLCDesign-Expert
Likelihood to Recommend
For now coders, I would emphasize them to use drag and drop functionality. Otherwise, WPS Analytics is a robust tool for app development and data visualization that offers multiple languages such as SAS, SQL, R, and Python.
AC
Adam Collier
Account Executive
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No answers on this topic
Pros
  • Data preparation and advanced analytics help us to gain insights on company data.
  • Data sharing and distributing securely.
  • Visualization of data with WPS Analytics saves time when making business decisions.
SS
Stefanie Smolinsky
Data Analytics Manager
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No answers on this topic
Cons
  • SAS functionality has to lack.
  • There's no online guideline, making it hard to solve problems.
Khairul Islam Tonmoy | TrustRadius Reviewer
Khairul Islam Tonmoy
Software Developer
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No answers on this topic
Alternatives Considered
To better understand the data I work with, I extensively use the data discovery and visualization tools available on my workstations, and I always go for the best. Unfortunately, some other tools does not offer any tutorials for the features, making it difficult and time-consuming to analyze data, mainly after it has been implemented. In addition to videos and articles, WPS Analytics provides comprehensive tutorials for each feature.
Khairul Islam Tonmoy | TrustRadius Reviewer
Khairul Islam Tonmoy
Software Developer
Read full review
No answers on this topic
Return on Investment
  • Reduction in operational costs since no data scientists are involved.
  • Time and effort have been reduced when analyzing data by using machine learning capabilities and natural language.
  • We have reduced time to value by bridging data processing to taking actions gap.
JH
Jonas Harmer
Business Development Specialist
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No answers on this topic
ScreenShots