Cloud Analytics 101: What Every Business Leader Should Know

Many businesses hope to build their data analytics capabilities in-house using their on-premises server. However, reality soon hits them when they realize it is a very cumbersome process with hidden costs and security challenges. And data without context and proper analysis is just like sawdust.   

For such companies, cloud analytics is the best option to take the burden of traditional analytics off their shoulders. Cloud data analytics has several use cases. You can use cloud analytics to do something as basic as tracking your website’s traffic to predict the trends on Wall Street using cloud-based big data analytics.  

2026 is months away, and it is a promising year for all things cloud computing. If your company still isn’t using cloud analytics platforms, then you’d better start planning the shift.   

In this article, we will prove to you why this transformation is necessary. We will cover every key aspect that business executives should know about cloud analytics, from its types to how to shift to cloud computing data analytics.  

What is cloud analytics? 

Cloud analytics is the practice of using cloud computing technologies to analyze and interpret business data. It is the opposite of traditional business intelligence (BI), where you need to own and maintain physical servers to interpret data.  

Today, cloud-based analytics is a service model where third-party vendors provide you with the infrastructure to perform BI and data analytics tasks. Providers of cloud analytics services abstract the complexity of setting up the cloud analytics environment. They provide you with the tools and services to perform business analytics on the cloud in a flexible and scalable way.  

Popular cloud data analytics platforms 

There are many cloud analytics vendors in the market. These service providers make data analytics in cloud computing simpler and more effective.  

Here are some of the big names in cloud data analytics platforms: 

1. SAP Analytics Cloud 

SAP Analytics Cloud is a major cloud data analytics platform used in a wide variety of industries. It combines BI and predictive analytics in a single integrated solution. SAP is especially great for Fintech companies that need real-time insights. 

2. Oracle Analytics Cloud 

Oracle Analytics Cloud lets users converse with their data. Really, it’s not hyperbole because the cloud analytics platform includes Oracle Analytics AI Assistant, which lets users ask questions in natural language and get back insights. 

The platform also offers analytics capabilities to different roles, like IT staff, service team, and decision makers. 

3. Salesforce Analytics Cloud 

Salesforce Analytics Cloud, now officially known as CRM Analytics, gives native cloud analytics capabilities to users within the Salesforce ecosystem. It is deeply integrated into Salesforce with an interactive user interface. 

The cloud analytics platform can analyze data from outside Salesforce as well. Using tools like MuleSoft and APIs, you can connect external data sources to analyze. 

4. Microsoft Power BI 

Microsoft Power BI is an excellent cloud data analytics platform for non-technical users. It is part of the Microsoft Azure ecosystem and delivered through both the web and mobile applications.  

It is one of the most affordable enterprise cloud analytics platforms for the functionality it offers. 

5. Tableau  

Tableau is known for its beautiful, interactive interface that helps users explore data dynamically. The platform was acquired by Salesforce, which is why it smoothly integrates with the CRM for all kinds of analytics needs.   

Users can connect Tableau to virtually any data source, like cloud warehouses, spreadsheets, SQL databases, or APIs. 

5 benefits of shifting your business to cloud analytics 

There are still a few businesses out there that haven’t adopted cloud computing data analytics. It is understandable because the transition to cloud analytics is not so easy, despite the accessibility of cloud services like AWS and Azure.   

However, you need to take this action sooner or later. And here are 5 compelling reasons why this decision will pay you in dividends.  

1. Scalability and agility in the age of IoT 

You’ll need a lot of cloud-based big data analytics in the coming future. Trust us, data volumes and workloads are of Biblical proportions these days with Internet of Things (IoT) and smart devices. Only cloud analytics can meet this increasing demand for scalability.   

Cloud data analytics gives you the elasticity, to put it in layman’s terms, where compute and storage scale automatically to match your needs. If you’re a business that deals with real-time customer data, shifting to cloud analytics is a matter of ensuring your survival. 

2. AI-powered analytics 

Adding the prefix “AI-powered” to anything is the neologism of our age. However, actually incorporating AI solutions into any system is not a piece of cake. Data analytics is the same. You would have to hire a team of AI/ML engineers to make your on-premises infrastructure AI-capable.  

Cloud analytics platforms, on the other hand, come pre-integrated with AI/ML capabilities such as predictive modeling, generative insights, and natural-language interfaces.  

For example, Oracle Analytics Cloud embeds ML and generative AI capabilities for business users. Users can apply one-click predictive models without needing a data scientist. 

3. Remote and hybrid work 

We all have our opinions about working from home. Most of our team prefer the office because they find it more productive. But remote work is now part and parcel of corporate life. Workforces are now global and mobile, which is why data accessibility needs to mirror this reality.  

Cloud analytics platforms allow secure, browser-based access from anywhere to ensure teams can collaborate on live dashboards regardless of location or device. Telling from first-hand experience, we have distributed teams across the United States, China, and Pakistan. Cloud analytics is critical to our global operations and cross-border setups. 

Orienting towards cloud analytics is ideal for making your organization’s work culture hybrid and flexible.  

4. Cost-effective and efficiency 

Upfront investments in traditional analytics can reach millions. This is simply out of the equation for small and medium enterprises (SMEs). Fortunately, data analytics in cloud computing flips that model. With pay-as-you-go or subscription-based pricing, cloud analytics services charge you only for what you use, which lets you scale resources up or down dynamically. 

Furthermore, even big IT corporations are leaning towards OPEX models for predictable costs that preserve liquidity. If you want to try new datasets without long procurement cycles or the infrastructure overhead, cloud analytics should be your top priority going into 2026.  

5. The cost of stagnation 

The Cambridge Dictionary describes the word laggard in Business English as “A company, organization, etc. that does something later, or improves less quickly, than others.” Now we don’t mean to use it in a negative way because we know transitioning to cloud analytics is an expensive and serious undertaking. 

However, delaying this transformation is now more expensive than undertaking it. Your legacy analytics systems can pile up hidden costs, outdated integrations, and security vulnerabilities.  

Moving to cloud data analytics will cost you much less than doing nothing in the long run. It also ensures that you remain relevant and toe-to-toe with your competitors in the industry. 

Types of cloud analytics 

People think of cloud computing as something intangible, but it’s really just rooms of very large computers. And that is why there are different types of cloud analytics depending on who controls and has access to these data centers.  

1. Public cloud 
2. Private cloud 
3. Hybrid cloud 

1. Public cloud 

Your data and analytics run on shared infrastructure owned by a third-party provider such as AWS, Microsoft Azure, or Oracle Cloud. On public clouds, your data is kept private, but IT systems are shared with anyone who uses or purchases their services. 

2. Private cloud 

A private cloud is usually behind a firewall and is only dedicated to your organization. It is not accessible to the general public and is similar to your company’s intranet. For example, VMware Cloud offers private cloud services where the underlying IT infrastructure is solely dedicated to your enterprise with complete isolated access. 

3. Hybrid Cloud 

A hybrid cloud is a combination of public clouds and private clouds. You can use a public cloud for analyzing non-sensitive data and a private cloud to perform cloud analytics on proprietary company data.  

Some companies even mix in on-premises systems for more control and security.  

Best practices to move your analytics to the cloud 

You need to focus on some key factors while making the move to cloud analytics. It will save you a lot of trouble later on. 

1. Structure your data 

You don’t have to move all your data to the cloud to use cloud analytics, but the cloud system needs a way to access it, either through integration, a hybrid setup, or a one-time transfer. 

Whatever you choose, the data needs to be clean and structured. If your data is messy or inconsistent, it can cause big downstream problems like duplicate records, reporting errors, or poor decision-making. 

Use data management tools to ensure that your key business data is standardized. It will greatly improve the performance of your cloud analytics tasks.  

2. Emphasize self-service 

Design your cloud analytics environment around self-service BI. And no, it doesn’t just mean training your employees how to access and use BI tools themselves. Data analytics in cloud computing is something better.  

Using cloud technology, people can do more on their own without IT support. For example, different team members can access data directly without the need for IT helpdesk support.   

This kind of self-service saves time, speeds up decisions, and keeps teams focused on insight instead of waiting for approvals. 

3. Be clear about costs 

When you move to cloud analytics, being open and clear about costs is essential. The first cloud bill often takes businesses by surprise. But usually it’s due to their own doing, like someone used an expensive storage option by mistake, or didn’t scale down resources when usage dropped.  

These small oversights can quickly turn into big surprises on your bill. Therefore, be clear about what different teams are spending and why. It helps people see which parts of the analytics environment are delivering value and which are just draining budgets.  

Using FinOps best practices brings cost visibility, which makes it easier to manage priorities or justify expenses. 

Conclusion 

Cloud analytics is, without any doubt, the future of data analysis. And that future is already here, as 2026 is just around the corner. Performing business analytics on the cloud is faster, more effective, convenient, and cheaper than traditional BI approaches. 

It will put your company in a better position for a business world that is in constant flux. But with cloud data analytics, you can make sense of these changes and how they relate to your enterprise.  

Xavor’s cloud analytics services do exactly that: Sensemaking in organizations using data. Our BI and data analysts interpret your business data to pinpoint what works, what doesn’t, and what needs to change.  

Contact us at [email protected] to discover how we can turn your data into actionable insights.