[Advertorial] Most organizations have now had their first experience with the cloud. The next phase is to cultivate maturity. In this series of three articles, we’ll introduce three best practices to get more out of the cloud and analytics. In the final part, we’ll explain why one can’t exist without the other and how you can efficiently bring both strategies together in a Cloud Center of Excellence.

For many companies, the cloud once sounded like the promised land for their demanding analytics and AI workloads. However, they often turned back from an easy journey, in part because the costs of the cloud were higher than expected. The path to the ultimate goal of cloud analytics is a steep climb full of hurdles; from the basics – migrating to the cloud – to the moment when your analytics projects actually start delivering benefits.

In the previous two articles in this series, we have already tackled some of the challenges on the way to the top of the pyramid. For example, we explained how FinOps practices optimize the costs of the cloud and align them with the value they generate for the business. In the second part, we discussed the importance of skills to drive the adoption of cloud and analytics.

Cloud and Analytics Competence Center

The overarching factor in this story is a Center of Excellence, a center of excellence that collects skills and best practices. Many companies already have a Cloud Center of Excellence (CCoE), but now they need to give analytics a prominent place in it. The goal of such a Center of Excellence is the same everywhere: to become a “cloud-centric” organization and use the “cloud” as a differentiator against the competition.

In fact, in this context, you could perfectly replace the cloud with analytics: an “analytics-centric” organization that uses “data analytics” to differentiate itself from the competition. Cloud and analytics are destined to come together in the same strategy. For example, in analytics, there are many requirements that are difficult or impossible to meet without the cloud. Consider the need for elasticity, the variety of internal and external data, the need for scalable platforms, etc. Look at the popularity of Large Language Models (LLMs). Such a model requires GPUs and to reduce costs, it makes sense to work with a cloud solution.

So, rather than treating analytics as a footnote or afterthought in your cloud story, integrate your analytics strategy into a shared cloud center of excellence (not the other way around). The cloud has different goals than analytics, but the path to get there is largely the same.

How exactly do you do that? Gartner describes the role of a Cloud Center of Excellence using three factors. We can also translate each of these components into analytics.

Enhance your cloud governance practices with analytics

Data protection, ethical and responsible applications of analytics, … In the context of the cloud, these are often not the first points to pay attention to, and this is even more true for analytics. All of these elements therefore deserve a place in an overall strategy. After all, a CCoE wants to protect the company and ensure that users use cloud tools correctly. If you apply analytics in this cloud, this principle also applies to all the tools you use in your data projects.

Governance of analytics in the cloud is also important in the context of FinOps. For example, tools need to be scalable and you want to be sure they are deployed at the right time. Operations teams therefore need to understand that analytics tools do not need to run 24/7 and therefore do not need to rely on the cloud all the time. Only knowing how to keep your tools up and running will help you keep your costs under control. Finally, tracking is also important. Conduct regular audits to ensure that employees continue to use their tools and models correctly.

To simplify these governance challenges, SAS has developed Model Cards. Compare it to a label showing nutritional value on product packaging. How pure is an analytics model? The tool shows how best to use a model and provides transparency by showing where the risks of potential bias are hidden. It shows that your organization cares about standardizing and centralizing analytics.

Build a community around cloud and analytics

A Cloud Center of Excellence consists of different roles and analytics is a must. Until now, data scientists have always worked in isolation, but now we need to expand this from the CCoE to a wider audience and develop skills around the combined use of cloud and analytics. Define best practices and look for analytics tools that enable self-service. The barrier to using analytics should be as low as possible.

A competence center needs to provide clarity with advice and action. As an extension of best practices, it is worth involving experts as internal consultants in business projects. You also need ambassadors. They are not necessarily in the driver’s seat, but rather overseeing the change from the old to the new world. One of their responsibilities is change management. Therefore, it is also important for cloud ambassadors to be able to participate in the discussion about analytics and not just mention it as a footnote. Only when analytics is part of a CCoE’s standard service can you develop a true data mentality.

Connect your company through your competence center

You want to build a cloud architecture efficiently? This is only possible if you also add an analytics component. Where will you migrate large amounts of data? How will you ensure that analytics delivers value to the business? If you leave this to the different business units, your company will never develop the right experience and a unified approach. Therefore, a Cloud Center of Excellence is the ideal place to connect the chief architect of the organization with the analytics needs.

The same applies to other critical roles in the company. Think of the CFO who wants to see results in order to allocate the right budgets, but also sales managers who want to understand what value analytics projects bring to the company. For both cloud and analytics, it is important that developments are communicated from the top down. The Cloud Center of Excellence is the ideal basis for involving senior management as stakeholders in analytics projects.

Ready for the promised land?

The adoption of analytics goes hand in hand with the adoption of cloud. Both strategies need to communicate with each other. A CCoE is the last piece of the puzzle we need to reach the top of the pyramid. On the other hand, starting with cloud and analytics from day one – or the base of that pyramid – is also a valuable concept.

Read more about the cloud analytics journey in this white paper and discover even more experiences and tips for reaching the promised land of cloud and analytics in the accompanying webinar.

This article is the last in a series of three articles on best practices for getting more out of the cloud and analytics. You can find the entire series here.

This is a commercial contribution from SAS. The publishers are not responsible for the content.