How to optimise cloud storage for SAS analytics

Facing difficulty is optimising and handling your cloud storage with SAS analytics? Following a plan makes it easy - here's our advice.

Why is optimising cloud storage important?

It might seem counterintuitive to talk about optimising cloud storage. After all, the cloud was built to host large amounts of data, why spend time and effort optimising storage on the cloud? But as the capacity of big data expands, servers will be pushed to their limits, and this will compromise the efficiency of data collection and analysis. When cloud storage is not optimised, it hinders efficiency in data analytics.

Several clients have come to us, seeking advice on how to optimise their environment for SAS analytics. One particular firm in fintech struggled with its data collection and analysis because cloud storage was not properly optimised. According to their CIO, working on their data analytics pipeline was like “Trying to swim up a sludge-filled river,” because completing basic functions was much harder than it should have been.

Given the connection between data analysis and cloud storage, organisations need to find ways to optimise their data storage to get the best results. Optimised cloud storage allows for responsive and efficient transfer of data, making data analysis more efficient. This maximises the value of SAS analytics and reduces operating costs.

Optimising cloud storage with SAS analytics

However, despite the obvious benefits, optimising cloud storage will not be easy, especially with SAS analytics. This is because SAS analytics works with several cloud databases, like AWS and Azure. To optimise storage, you need to be familiar with these different platforms. However, there are still some things that can be done to optimise storage, in general.

Minimise data duplication and replication

One of the most common methods for optimising cloud storage is minimising data duplication and replication. Data duplication has several steps in the process, like chunking and securing hash algorithms. But the advantages are significant because it essentially eliminates all duplicates from the dataset, making it easier to work with and providing high-quality data for SAS analytics platforms to process.

Configure an auto-scaling solution

Autoscaling is one of the best practices for optimising cloud storage. When auto-scaling solutions are implemented, the cloud platform scales automatically to match the volume of the workload.

Autoscaling makes cloud storage more efficient because cloud resources can expand and contract dynamically to match demand, reducing the workload for SAS experts and technical users.

You can configure auto-scaling solutions on AWS and Azure, although it should be noted that theprocess for implementing auto-scaling will be different for both platforms.

Balancing workloads

At its core, optimising the cloud is about maintaining a balancing act between workload performance, costs and compliance. The goal is to balance workload against infrastructure in real-time to attain efficiency. The challenge for optimising the cloud for SAS analytics is that no single strategy is the same. However, there are some things you can do to optimise cloud storage.

Workload modelling and optimisation

A significant chunk of cloud optimisation is analysing patterns in the workload, including past use and operational costs, in a process called workload modelling. Current use is then compared against the recommended configurations that would deliver the ideal workload for the platform.

Encourage transparency

When cloud platforms grow, they become more complex, compromising transparency. When transparency is compromised, it becomes much harder to maintain an efficient cloud platform. So, it’s important to improve oversight and transparency across the board to make the sharing of data much easier. Furthermore, it improves efficiency in cloud storage methods.

Optimising the cloud is an ongoing process

It’s important to understand that optimising cloud storage is an ongoing process, so its best to invest in tools to make the process easier. Workflow automation can help significantly with the process because it helps SAS professionals identify any unused or partially idle resources and can either use these resources or shut them down.

Cloud storage methods to keep in mind

As many of you know, optimising cloud storage comes with several benefits that could help your clients reduce costs and improve operational efficiency. However, this is easier said than done because SAS Analytics uses different cloud databases, like Azure and AWS, to get the job done. However, by using the right tools, optimising cloud storage becomes a more efficient process, which is crucial for organisations working with large volumes of data.


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