Bringing SAS Analytics Programs into the World of Modern Development

Altair SLC runs programs written in SAS language syntax without translation and without needing to license third-party products.

The SAS language has been synonymous with data mining and data science for decades. And many organizations have developed SAS language programs over the past 20 years that are vital to their operations.

But SAS programming faces a generational change. Modern analytics uses other languages like Python, R, and SQL. And today, many organizations are under pressure to reduce costs and find alternatives for handling their SAS language requirements.

Altair offers a way to address both issues. Its Altair SLC runs programs written in SAS language syntax without translation and without needing to license third-party products.

Additionally, Altair SLC provides great flexibility to match any organization’s efforts. It supports the programming languages found in businesses today. Specifically, Altair SLC handles programs, workflows, and models that combine the SAS language and SQL, Python, and R languages. Its built-in SAS language compiler runs SQL and SAS language code and utilizes Python and R compilers to run Python and R code and exchange Pandas and R data frames.

Another form of flexibility is that Altair SLC runs on any platform. It works on IBM mainframes and in the cloud, and on servers and workstations running a host of operating systems. It also supports remote job submissions and can exchange data between mainframe, cloud, and on-premises installations.

The solution offers expanded language support: In particular, Altair SLC’s built-in SAS language compiler supports SAS language and macro syntax. It includes procedure support for statistics, time series analytics, operational research, machine learning, matrix manipulation, graphing, and output delivery. Additionally, it doesn’t require third-party middleware to process applications containing the SAS language.

Making the change to Altair SLC

Altair recommends a five-step process to move to Altair SLC. That process includes:

Step 1: Perform a system analysis to understand how all the components in the current system work together, including computing platforms, applications, the number of systems to consider, and the data itself.

Step 2: Perform a code analysis to examine the syntax used in existing applications. Altair provides a code analysis tools to do this work. The tool generates reports without executing SAS language programs or accessing data sources. It can analyze thousands of SAS language programs containing millions of lines of code in just a few minutes.

Step 3: Plan the migration by inventorying business requirements, known gaps, current documentation, applications, instances, databases, and code. Altair offers services to help with this work.

Step 4: Develop a pilot project to prove the migration’s viability.

Step 5: Roll out the migration. This part of the process should include training. And once the migration is complete, businesses should retire assets that are no longer needed.

See also: Frictionless AI: The Key to Delivering on AI’s Promise

Putting Altair SLC to use

Users can use Altair SLC in batch or standalone mode to execute programs and models or use it with Altair Analytics Workbench, a GUI/IDE that supports traditional coding and no-code methods to develop, update, and maintain programs and models written in the SAS programming language.

Altair SLC powers the solution. It gives users a drag-and-drop workflow environment to develop models and programs without writing any code. Developers can use Python, R, or SQL code in their SAS language programs. And the platform incorporates data discovery capabilities.

The Analytics Workbench provides machine learning support for supervised and unsupervised learning, including decision trees, clustering, regression analysis, and neural networks. These capabilities let users build and test machine learning models and automatically generate error-free code for production use.

The combined features and capabilities make the solution useful to users with a wide range of skills. It allows data engineers, data analysts, data modelers, data scientists, and citizen data scientists to develop critical data analytics models and run workflows. For example, people with no coding skills can use the solution’s visual workflow to extract and transform data from various disparate sources and produce reports. At the same time, experts can perform advanced analytics tasks using the platform’s coding environment.

The solutions in action

An example of the power of Altair Analytics Workbench and Altair SLC is Altair customer Vestigo, a London-based financial consultancy. Vestigo develops credit risk, portfolio analysis, and stress testing workflows and machine learning models for lenders in the U.K. and Europe. Its clients include major financial institutions, private equity and investment funds, and specialist lenders.

It needed an efficient way to deploy analytics and deliver data-driven insight quickly for clients varying in size from regional operations to lenders with loan portfolios exceeding $5 billion. The team has many years of experience developing and deploying models built using the SAS language and has clients with libraries of existing SAS language models and needed a way to utilize code built in several languages into deployable — and maintainable — models.

Vestigo uses Altair Analytics Workbench to develop and maintain models and programs written in the SAS language to accomplish this. IT can work with clients regardless of what language the client used to build their models since the Analytics Workbench can handle Python, R, and SQL in addition to the SAS language. Specifically, Vestigo can combine modules built in any of the four languages into updated models.

Altair SLC runs programs written in SAS language syntax without translation and without needing to license third-party products. That reduces Vestigo’s capital costs.

A final word

Modern developers of analytics and ML tools typically use free-to-use resources like Python, R, and SQL to conduct their work. But many companies have decades worth of efforts in developing business-critical programs using the SAS programming language.

Altair Analytics Workbench and Altair SLC offer a way to meld the best of both worlds together. The workbench gives developers of any skill set a drag-and-drop environment to create programs and build data analytics workflows. Altair SLC lets them use Python, R, or SQL code in their SAS language programs. 

Altair claims that with such capabilities, businesses that migrate to Altair SLC can realize returns on investment often within a year and cost savings of between 50% to 70%.