What could discourage organisations from adopting an analytics cloud platform?

An analytics cloud platform is a vital asset for any business. With the world forced indoors due to the COVID-19 pandemic, organisations need to find ways to meet their data analytics needs, and many analytics providers have stepped up to the plate. For example, SAS uses deployment patterns like containers and Kubernetes to orchestrate and streamline deployments across major cloud infrastructure providers like Microsoft and Google.

However, despite this immense progress, there are still several obstacles that prevent private and public organisations from adopting an analytics cloud platform. Anticipating these objections can help SAS analytics engineers proactively address them.

The challenges of implementing an analytics cloud platform

Data security

Security is one of the biggest concerns for organisations looking at an analytics cloud platform. Analytics engineers have to maintain a balance between tight security protocols and sufficient flexibility to make working with data easier.

After all, most companies don’t want their information stolen, but neither do they want a rigid system that makes standard operations difficult to carry out. To maintain balance, analytics platforms must have built-in flexibilities that allow them to integrate popular security tools.

Furthermore, since security threats are always evolving, platform developers need to keep an eye on the latest security trends and safeguards to assure potential customers that their information is safe from evolving dangers.

They work on any system

An analytics cloud platform should seamlessly integrate into an organisation’s processes. Organisations want to use their current technologies and processes, alongside the new cloud platform, instead of having to revamp their entire infrastructure to accommodate it.

The challenge for most analytics engineers is to ensure that their cloud platform is not confined to a specific operating system or hardware requirement because it reduces accessibility, locking out organisations who might have been interested in the platform.

However, creating a system like this is not an easy task because it requires the system to be self-aware and make decisions based on available resources.

For example, should the system use in-stream processing or a single-threaded processor? If an analytics cloud platform is going to work, the system needs to maintain processes, while scaling resource use up and down when needed, without intervention from programmers.

Operationalising data pipelines

One big concern for organisations is the work involved in getting data pipelines ready for use. As any cloud analytics engineer knows, operationalising a data pipeline complete with fault-tolerant recovery and full monitoring is not a task that can be completed overnight.

Establishing multi-cloud and hybrid workflows, setting parameters for dynamic control, debugging production runs, resource management and fault tolerance are just some of the operations that need to be completed before an analytics cloud platform is ready.

The effort needed to operationalise pipelines is an obstacle because most organisations are not clear about how all this technical work will affect their scheduling and production. They want to know how soon they can shift their data to the cloud, and use it to improve production processes.

As cloud analytics engineers, it’s your job to make the process as transparent as possible to build confidence with customers and encourage them to invest in the cloud platform.

Managing hybrid environments

A hybrid environment is often used as a solution for an organisation that needs 100% uptime performance. However, this arrangement comes with several challenges that hinder the appeal of the analytics cloud platform.

The main reason being that it takes a lot of work to operationalise the data pipeline across multiple cloud platforms and on-premise environments. Analytics engineers need to devise ways to optimise processes, to ensure they are as timely and efficient as possible.

Migration needs to be optimised

Migration from legacy systems, such as data warehouses can be time consuming and expensive. Data can be lost or corrupted if the migration process is not done properly. When shifting to the cloud, it is important to set up proper procedures, including backing up data.

Analytics programmers and engineers need to consider all aspects of platform migration and plan out the process in detail, which includes backing up data in a secure fashion.

Maintainability and governance

Who is responsible for monitoring cloud systems? How are servers going to be upgraded and maintained if applications need to be up 100% of the time? Establishing who is responsible for ownership can be challenging for many organisations, especially if they are not experienced in dealing with cloud platforms.

In my experience, the best way to resolve this uncertainty is to keep the terms as simple as possible and remain transparent. As analytics programmers and engineers, it can be very difficult not to discuss governance and maintainability without bringing in the technical terms.

But most clients are often put off by this method of communication, so it’s best to state the terms of maintenance and governance in a language that’s as simple as possible.

Addressing the challenges of cloud systems in analytics

An analytics cloud platform is an important asset, but it is filled with challenges that often obstruct companies from undertaking the platform. However, if we can anticipate these problems and address them, we can remove the obstructions that discourage companies from adopting cloud platforms.

The ideal analytics cloud platform allows businesses to leverage powerful analytics platforms without the need for a programming team and effortlessly integrates itself into business operations.

Analytics platforms – when is it time to change yours?

A barrage of changes in the world of data has sent organizations scrambling to manage their requirements through comprehensive analytics platforms. In this day and age, organisations are increasingly under competitive pressure to not only acquire customers but also understand their customers’ needs to be able to optimise customer experience and develop long-standing relationships.

Data analytics platforms help organizations harness their data and use it to identify new opportunities. That, in turn, leads to smarter business moves, more efficient operations, higher profits, and happier customers. Research done by MIT Management Review and SAS back in reports that 67% of companies gain a competitive advantage by using analytics platforms. Each year, this percentage grows exponentially with more companies opting every day to adopt an effective analytics platform.

With such an emphasis on analytics, it’s important to know when you need to make a shift. Here are a few signs that indicate its time to change your analytics platform.

Is your company using the right analytics platform to complement your industry?

More often than not companies are not fully utilising their current data analytics platforms because their platforms are not complementing their company’s needs or taking into account the industry they are in. It is no secret that data analytics can prove to be exponentially valuable for companies of all sizes. After all, 61% of corporate decision-makers have said they struggled to access or integrate the data they needed last year. This begs the questions, are they using the right platforms to support their company within the context of their industry?

For example, if you’re in insurance, you need greater visibility over your claims and how your payouts are taking place. This needs to be facilitated by your platform. Similarly, these requirements will vary from one industry to another. Therefore, it’s imperative that your analytics platform has the capacity to uniquely cater to your industry-specific needs.

Expansion to multiple sites means you need a platform that can grow with you

Businesses are constantly growing – especially ones looking at cross-regional expansion. This level of growth will require much more than what an ordinary data analytics platform can offer. The ability to share and host data through multiple sites is integral for operating seamlessly and effectively.

In this day and age, companies are on the lookout for effective data analytics platforms that accommodate multiple sites. Analytics platforms like SAS facilitate the accommodation of multiple sites in this manner.

This renowned platform has a deep bench of analytics solutions, bolstered by experts with broad industry knowledge, that can facilitate any company in seeking immediate value from data across multiple sites and location. Identify what’s working, fix what isn’t, and make more intelligent decisions. This will drive relevant change.

A comforting statistic to mull over is that over 90 per cent of the largest global firms have SAS – organizations and companies like Bank of America, the World Wildlife Fund and Honda have all adopted SAS into the fold of their companies and are reaping the benefits of this intricately designed analytics platform.

You’re not happy with the support services

Analytics companies know that not everyone is as data-minded as they are, so they put a lot of effort into building platforms that have interfaces that are simple and easy to use. You can get most of the information you need with very little effort. However, even with this emphasis on user experience, some analytics users require additional assistance and guidance.

It’s with this in mind that many companies rely on support services that come with analytics platforms – as opposed to standalone platforms themselves. One major advantage of an analytics platform like SAS is that it has many partners around the world capable of both selling SAS software and facilitating services. As a company that offers comprehensive support services in this regard, we are one of the first organisations in Australia to obtain the Visualisation competency badge from SAS.

To accommodate the ever-changing landscape of data analytics, we are constantly developing new, efficient, and creative ways to improve the insights companies obtain through their SAS systems.

Key takeaways

The analytics industry is evolving rapidly, both in terms of the data it can collect and the myriad of ways software can slice and dice this data to help you find actionable trends. This data is there for the taking and you can easily use it to optimise your business’ operations – especially with SAS. Additionally, keep in mind that your competitors are doing this too — so be sure not to get left behind.

Businesses, both large and small, can benefit from analytics. Whether you sell one product or a thousand, whether you’re a solo entrepreneur or a multinational conglomerate, the principles, techniques, and goals of analytics are the same — identify which business activities generate revenue, and use this to guide future decisions.
For more information on how you can supercharge your company’s impact through an effective and comprehensive data analytics platform, visit our site.