Altair SLC is a software platform from Altair Engineering that supports machine learning model lifecycle management. It provides capabilities for version control, monitoring, and collaboration so teams can manage their models effectively. This platform allows data scientists and engineers to track changes, share insights, and maintain model integrity throughout its lifecycle. Altair SLC features advanced tracking for model performance, tools for collaborative projects, and integration with existing data pipelines. Key capabilities: version control model monitoring collaboration tools integration support performance tracking Best for: data science teams that need to manage and maintain machine learning models efficiently.
Altair SLC, developed by Altair Engineering, is a powerful data analysis and analytics platform designed to support users transitioning from traditional SAS language environments to open and modern ecosystems. Its core purpose is to execute programs written in SAS language syntax without requiring a base SAS license, which makes it particularly appealing to organizations looking to cut costs while maintaining compatibility with legacy analytics codebases. Key features of Altair SLC include its high-performance engine for running SAS language programs, support for open-source integration (notably Python and R), and its ability to deploy workflows in modern environments such as cloud, containers, and distributed infrastructures. The user interface of Altair SLC is built to facilitate seamless interaction for both traditional SAS programmers and modern data scientists. While the command-line and scripting environment remains familiar for experienced users, newer users benefit from an integrated development environment (IDE) that streamlines code writing, execution, and debugging. Navigation is straightforward, and code syntax highlighting, auto-completion, and real-time error detection tools are integrated to improve productivity.
Runs programs written in SAS language and macro syntax without requiring translation or third-party licenses, ensuring seamless migration and continued use of existing SAS code.
Allows users to combine program modules built in SAS language, Python, R, and SQL within a single, coherent platform, breaking down data science language barriers.
Can be installed and used in the cloud (including Google Cloud Marketplace), on-premises, on mainframes, or in hybrid architectures, providing versatility for various IT infrastructures.
Offers low- and no-code tools, visual workflow development (with Altair Analytics Workbench), and assisted deployment through open web APIs to shorten development and deployment cycles.
Connects to virtually any data source, including cloud services, Hadoop, data warehouses, databases, SAS language files, SPSS, Excel, CSV, and other file-based formats, with no limits on data volumes.
When integrated with Altair SLC Hub, it allows for scheduling jobs at specific times and days, and visually building execution decision pipelines with defined rules and conditions.
Provides code analysis tools to analyze thousands of SAS language programs quickly and offers expert support throughout the migration process (assessment, proof of concept, rollout).
Altair SLC's core functionality is a SAS language compiler that can run existing SAS programs, macros, and procedures (for statistics, time series, machine learning, graphing, ODS, etc.) without any translation or third-party SAS licenses.
Integrates SAS language, Python, R, and SQL within a single environment, allowing users to combine code from different languages in the same program or workflow and seamlessly exchange data between them.
Can be installed and deployed in various environments including on-premises, in the cloud (e.g., Google Cloud Marketplace), on mainframes, or in hybrid setups, accommodating diverse IT infrastructures.
Connects to virtually any data source, including cloud services, Hadoop, data warehouses, various databases, SAS, SPSS, Microsoft Excel, CSV, and other file formats, with no limitations on data volume.
Leverages advanced processing capabilities for large datasets, including support for SAS Cloud Analytics Services with SAS Viya connections and automatic detection/utilization of grid environments with SAS 9 connections.
Provides user-friendly interfaces and wizards to simplify data integration, preparation, analysis, and reporting, empowering business users who may not have extensive coding experience.
Integrates with Altair Analytics Workbench, an IDE that offers a drag-and-drop visual workflow builder for creating, maintaining, and executing programs and models.
Offers a sophisticated IDE within Analytics Workbench with a code editor, syntax highlighting, autocompletion, code templates, and project management facilities for those who prefer to write code.
Includes tools like a data profiler to explore and validate data, count missing values, display univariate statistics, and visualize correlations without writing code.
Supports visual development of supervised and unsupervised machine learning models (e.g., decision trees, clustering, regression) with automatic code generation for production.
When integrated with Altair SLC Hub, it enables scheduling of analytical jobs for specific times and days and allows users to visually build complex execution decision pipelines with defined rules and conditions.
Altair SLC Hub simplifies the deployment of analytical programs, models, and workflows as scheduled tasks or for on-demand execution by internal or external users.
Provides point-and-click wizards within Altair SLC Hub to create RESTful APIs from deployed analytics, allowing easy integration with other applications and prompting users for inputs.
Offers robust features for managing users and controlling access to data sources and deployed applications, including audit logs for user actions and synchronization via LDAP with Active Directory Services.
Includes code analysis tools that can quickly assess thousands of SAS language programs for compatibility, along with expert support for the complete migration process (assessment, proof of concept, rollout).
Generates formatted output in various destinations like HTML, PDF, and RTF, allowing for flexible reporting.
Implements centralized, IT-managed role-based security to ensure that users have appropriate and secure privileges for accessing corporate data.
Facilitates smoother development and operations workflows with assisted deployment through open web APIs and simplified end-to-end analytics processes.
Offers access to a community forum, technical documents, webinars, how-to channels, and direct support for assistance.
Provides an extension for Visual Studio Code, allowing users to start SLC sessions, submit SAS language programs, view logs and ODS output, and browse datasets within the VSCode environment, including Notebook support.
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Altair SLC is a software platform from Altair Engineering that supports machine learning model lifecycle management. It provides capabilities for version control, monitoring, and collaboration so teams can manage their models effectively. This platform allows data scientists and engineers to track changes, share insights, and maintain model integrity throughout its lifecycle. Altair SLC features advanced tracking for model performance, tools for collaborative projects, and integration with existing data pipelines. Key capabilities: version control model monitoring collaboration tools integration support performance tracking Best for: data science teams that need to manage and maintain machine learning models efficiently.
Does Altair SLC have an in-app market place?
Yes
How many Mini-Apps in the marketplace?
1
N/A
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