Why SAS analytics for containers is a game-changer in data collection

SAS analytics for containers

The advent of container technology is revolutionising software development and data analytics because these software units allow you to run applications on different platforms, including desktops, physical servers and virtual servers. 

Containers present a consistent interface that allows developers to easily migrate software to different environments making the work easier for your IT teams and analysts. 

While container technology does benefit many development workflows, what does using SAS analytics for containers mean in data collection? 

Today, you can implement and manage your SAS analytics tools within containers, making it easier to manage critical business data in a unified platform. 

In this post, we explore how SAS for containers is transforming data management processes across the globe. 

Adoptable options for more than one software container versions

One of the primary advantages of using SAS Analytics for containers is the flexibility it offers to the users. 

SAS Analytics has the tools to help you deploy the SAS Viya platform on Docker and Kubernetes.

You can even get support for Docker deployment on SAS 9 with the SAS Recipe, a set of instructions that lets you access the traditional SAS software depot, extract the software components to perform a Docker image build, and create dedicated containers.

This approach enables the customisation of the operating system to the way you desire for building the Docker image and running the container. 

With an integrated platform, developers can access various tools they can deploy in different contexts. For data analysts, this means readily available predictions and insights delivered without bottlenecks. 

Analysts get self-access to data platform

In most traditional cases, data analysts rely on the expertise of the IT team to access the data hubs. 

With container-based data science platforms like Domino Data analysts, analysts have access to the SAS platform without assistance or approval from the IT team. 

Once the container image for SAS is deployed, anyone in your analytics team can access and use it to gain insights faster. 

Unlike the conventional SAS platforms, SAS for containers has a wide range of container images that include a combination of SAS and open-source software—analysts can easily leverage a range of tools necessary for data collection, examination and analysis.

You can easily upgrade to a new version of the software

Another benefit of using SAS Analytics for containers is that you don’t need to worry about new updates. If you want to upgrade to a new container, you can create a new image with the latest version and use it to build an updated container.

This feature gives you the chance to upgrade your software without disrupting other users, eliminating the need to wait for weekends or pausing your operations midweek to deploy new updates. 

Additionally, you can also test the new container and deploy it when it is stable and optimised. It is also possible to keep multiple container images for different versions; users can test their code against different versions for stability and efficiency before deployment.

Moreover, you can implement just the required SAS software, analytical models, and supporting code in the form of a small execution engine bundled into a lightweight container.  

Establish a high-end data collection process with SAS for containers

Data collection is the heart of business strategizing. 

That’s why optimising the data collection process using SAS analytics for containers guarantees an efficient data analytics pipeline, helping you establish simplified and streamlined business operations within your corporation. 

With our range of managed processes, we can help you access and establish a seamless and sophisticated SAS experience. 

If you would like to know more about how you can transform your corporation with better data collection, don’t hesitate to give us a call to learn more about utilising SAS analytics for containers. 

Ari Vivekanandarajah

Ari Vivekanandarajah

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