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Altair SLC

Altair SLC
Formerly WPS Analytics

Overview

What is Altair SLC?

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…

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Recent Reviews
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Pricing

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What is Altair SLC?

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…

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  • Free/Freemium Version
  • Premium Consulting/Integration Services

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What is IBM Cognos Analytics?

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Product Details

What is Altair SLC?

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.

The vendor says their software is versatile and is used by a broad spectrum of users including: business analysts; data scientists; capacity and performance planners; business users; executive management. Additionally, the vendor says high reliability and execution performance means WPS software is trusted to run critical production systems in many large organisations. Altair SLC is also at home in a modern data science team where it is used for advanced predictive modeling tasks to understand data and to guide decision makers to make better choices.

Altair SLC works with data in files, databases, data warehouses, Hadoop clusters and cloud storage with special connectors designed to take advantage of any processing and storage technology.

Altair SLC Features

Data Discovery and Visualization Features

  • Supported: Pre-built visualization formats (heatmaps, scatter plots etc.)
  • Supported: Predictive Analytics
  • Supported: Support for Machine Learning models
  • Supported: Pattern Recognition and Data Mining
  • Supported: Integration with R or other statistical packages

BI Standard Reporting Features

  • Supported: Customizable dashboards

Ad-hoc Reporting Features

  • Supported: Drill-down analysis
  • Supported: Formatting capabilities
  • Supported: Predictive modeling
  • Supported: Integration with R or other statistical packages

Report Output and Scheduling Features

  • Supported: Publish to Web
  • Supported: Publish to PDF
  • Supported: Report Delivery Scheduling

Altair SLC Technical Details

Deployment TypesOn-premise
Operating SystemsWindows, Linux, Mac, AIX, Solaris, z/OS
Mobile ApplicationNo
Supported LanguagesEnglish, French, Japanese

Frequently Asked Questions

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.

SAS Viya, Microsoft BI (MSBI), and IBM SPSS Statistics are common alternatives for Altair SLC.

Reviewers rate Report Delivery Scheduling and Predictive Analytics highest, with a score of 9.4.

The most common users of Altair SLC are from Small Businesses (1-50 employees).
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Comparisons

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Reviews and Ratings

(9)

Reviews

(1-4 of 4)
Companies can't remove reviews or game the system. Here's why
Khairul Islam Tonmoy | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User
Incentivized
WPS Analytics is a unique platform that works for data engineers, analysts, data scientists, modelers, and DevOps. We have relied on this product for years, primarily as a replacement for Base SAS, and we have found it virtually flawless. It offers many data integration and analysis packages and supports SAS, SQL, Python, and R in the same interface. When I've run into issues or needed additional guidance, the support team has always been quick to respond and helpful. It enables the user to visually design processing strings through configurable drag and drop flow, allowing the user to write calls manually.
  • Workflow visualization, data prep, and advanced analytics help us analyze company data.
  • High-performance data processing powers secure data sharing and distribution.
  • Visualizing data with WPS Analytics saves time on business decisions and self-service portals.
  • SAS functionality has to lack.
  • There's no online guideline, making it hard to solve problems.
WPS Analytics allowed our company's business users to keep using their existing programs while getting similar results with much less learning time. It's a great accomplishment when software for business users is changed—excellent relationships with providers and other salespeople. As a SAS user, I needed an interpreter for the SAS language, and WPS has more packages and a lower price than any other company I could find, so I decided to go with it.
  • Visual drag-and-drop workflow is available in WPS Analytics.
  • End-users can access and visualize data with self-service.
  • It includes data discovery and governance capabilities.
  • Additionally, it's compatible with third-party applications such as R and APIs.
Data Discovery and Visualization (2)
85%
8.5
Pre-built visualization formats (heatmaps, scatter plots etc.)
80%
8.0
Predictive Analytics
90%
9.0
BI Standard Reporting (1)
80%
8.0
Customizable dashboards
80%
8.0
Ad-hoc Reporting (3)
80%
8.0
Drill-down analysis
80%
8.0
Formatting capabilities
80%
8.0
Integration with R or other statistical packages
80%
8.0
Report Output and Scheduling (3)
83.33333333333334%
8.3
Publish to Web
80%
8.0
Publish to PDF
80%
8.0
Report Delivery Scheduling
90%
9.0
  • Using machine learning and natural language to analyze data saves time and effort.
  • Standard reporting and business intelligence help us reduce workload and make data-driven decisions.
  • Drag-and-drop workflow saves time when different languages like SQL and SAS make it easier to code and prepare data.
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.
SAS Visual Analytics, Power BI For Office 365 (discontinued), Google Cloud Virtual Private Cloud (VPC)
Score 10 out of 10
Vetted Review
Verified User
Incentivized
WPS Analytics is a single unified analytics solution that we have employed in some departments at my current corporation. It enables me to create data-focused applications with zero or low coding and visual workflows.
  • WPS Analytics is powered with high performance data processing engine.
  • Reusable data models save finances and time.
  • Self-service data analyzation portals.
  • I can't complain at the moment since the vendor support team and online WPS communities help me get rid of issues rapidly.
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.
  • Interactive modeling tools.
  • Collaboration capabilities: Help share workflows.
  • Drag and drop functionality for workflow automation.
  • Data discovery and governance.
Data Discovery and Visualization (2)
100%
10.0
Pre-built visualization formats (heatmaps, scatter plots etc.)
100%
10.0
Predictive Analytics
100%
10.0
BI Standard Reporting (1)
100%
10.0
Customizable dashboards
100%
10.0
Ad-hoc Reporting (3)
100%
10.0
Drill-down analysis
100%
10.0
Formatting capabilities
100%
10.0
Integration with R or other statistical packages
100%
10.0
Report Output and Scheduling (3)
100%
10.0
Publish to Web
100%
10.0
Publish to PDF
100%
10.0
Report Delivery Scheduling
100%
10.0
  • Model analyser help us choose the best that suit our needs.
  • Drag and drop workflow reduce time when coding.
  • Data prep is simplified by mixture of languages such as SQL and SAS.
Although we didn't implement datapine, we evaluated it but it was way too expensive compared to WPS Analytics.
Score 10 out of 10
Vetted Review
Verified User
Incentivized
WPS Analytics is utilized in a few selected departments to unify data in one central source from disjointed data centers. Implementation was super easy and didn't require third-party service providers to deploy.
  • Workflow visualization.
  • Data preparation, modeling, analyzation and visualization.
  • With WPS Analytics, it has been effective to make data-centric decisions by using machine learning capabilities.
  • Currently, I barely encounter challenges when using WPS Analytics although I don't use it on a daily basis. There's no functionality or feature that needs more improvement.
WPS Analytics best suits all business users that require to access old and new data from multiple sources such as Hadoop, data warehouses, WPS & SAS datasets into one single solution.
  • Interactive modeling tools enable us to save time when analyzing data since we reuse models in real-time.
  • WPS Analytics offers multiple natural languages such as SAS, SQL, R and Python.
  • Self-service capability help end users to access and visualize data on their own.
  • No code and low code environment with drag and drop workflow.
Data Discovery and Visualization (2)
100%
10.0
Pre-built visualization formats (heatmaps, scatter plots etc.)
100%
10.0
Predictive Analytics
100%
10.0
BI Standard Reporting (1)
100%
10.0
Customizable dashboards
100%
10.0
Ad-hoc Reporting (3)
100%
10.0
Drill-down analysis
100%
10.0
Formatting capabilities
100%
10.0
Integration with R or other statistical packages
100%
10.0
Report Output and Scheduling (3)
100%
10.0
Publish to Web
100%
10.0
Publish to PDF
100%
10.0
Report Delivery Scheduling
100%
10.0
  • 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.
Unfortunately, Tableau Desktop does not offer tutorials for the features making it hectic and complicated to analyze data, mainly after implementation. WPS Analytics offers detailed tutorials in form of videos and articles for all features.
Score 9 out of 10
Vetted Review
Verified User
Incentivized
It's almost two years now ever since I started using WPS Analytics at the workplace in my current organization. WPS Analytics [hasn't been] used company-wide, but nearly half of company units utilize it to perform several processes like predictive analysis, data preparation, ETL, data discovery, and modeling.
  • 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.
  • WPS Analytics does not have on-premises applications for PC, tablets and the worst part is a mobile application, which would help end-users visualize data on the go from anywhere.
WPS Analytics had helped us develop, deploy and govern data analytics applications across the organization in a central location. This comes along with tons of benefits such as data quality improvement by removing duplication.
  • Simple visual drag-and-drop workflow capabilities.
  • Self-service portal: This equips end-users with data visualization that help in analyzing data without involving third-party service providers.
  • Cloud analytics capabilities: predictive modelling, augmented analytics etc.
  • BI standard and Ad-hoc reporting tools.
  • Integration with R, APIs and other applications.
Data Discovery and Visualization (2)
100%
10.0
Pre-built visualization formats (heatmaps, scatter plots etc.)
100%
10.0
Predictive Analytics
100%
10.0
BI Standard Reporting (1)
100%
10.0
Customizable dashboards
100%
10.0
Ad-hoc Reporting (3)
100%
10.0
Drill-down analysis
100%
10.0
Formatting capabilities
100%
10.0
Integration with R or other statistical packages
100%
10.0
Report Output and Scheduling (3)
100%
10.0
Publish to Web
100%
10.0
Publish to PDF
100%
10.0
Report Delivery Scheduling
100%
10.0
  • Reduction in operational costs for analyzing data.
  • Machine learning capabilities help us automatically analyze data without involving any manual process.
  • Standard reporting enhanced by business intelligence helps us reduce workload while viewing company financial position to make data-centric decisions.
I use a lot of data discovery and visualization tools at workstations to help me gain deep insights into data. WPS Analytics doesn't vary much from all the DVD tools that I have listed, I always go for the best.
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