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<\/div>\nMany 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.\u00a0\u00a0\u00a0<\/p>\n
For such companies, cloud analytics is the best option to take the burden of traditional analytics off their shoulders.\u00a0Cloud data analytics<\/strong><\/a>\u00a0has several use cases. You can use cloud analytics to do something as basic as tracking your website\u2019s traffic to predict the trends on Wall Street using cloud-based big data analytics.\u00a0\u00a0<\/p>\n 2026 is months away, and it is a promising year for all things cloud computing. If your company still\u00a0isn\u2019t\u00a0using cloud analytics platforms, then\u00a0you\u2019d\u00a0better start planning the shift.\u00a0\u00a0\u00a0<\/p>\n 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.\u00a0\u00a0<\/p>\n Cloud analytics is the practice of using\u00a0cloud computing<\/strong><\/a>\u00a0technologies to analyze and interpret business data. It is the opposite of traditional\u00a0business intelligence<\/strong><\/a>\u00a0(BI), where you need to own and\u00a0maintain\u00a0physical servers to interpret data.\u00a0\u00a0<\/p>\n 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.\u00a0\u00a0<\/p>\n There are many\u00a0cloud analytics vendors\u00a0in the market.\u00a0These service providers make data analytics in cloud computing simpler and more effective.\u00a0\u00a0<\/p>\n Here are some of the big names in cloud data analytics platforms:\u00a0<\/p>\n SAP Analytics Cloud is a major cloud data analytics platform used in a wide variety of industries.\u00a0It combines BI and predictive analytics in a single integrated solution. SAP is especially\u00a0great for\u00a0Fintech<\/strong><\/a>\u00a0companies that need\u00a0real-time insights.\u00a0<\/p>\n Oracle Analytics Cloud lets users converse with their data.\u00a0Really,\u00a0it\u2019s\u00a0not\u00a0hyperbole\u00a0because the\u00a0cloud\u00a0analytics platform includes Oracle Analytics AI\u00a0Assistant,\u00a0which lets users ask questions in natural language and get back\u00a0insights.\u00a0<\/p>\n The platform also offers analytics capabilities to\u00a0different roles, like IT staff,\u00a0service team,\u00a0and\u00a0decision makers.\u00a0<\/p>\n Salesforce\u00a0Analytics Cloud, now officially known as CRM Analytics, gives native\u00a0cloud\u00a0analytics capabilities\u00a0to users within the\u00a0Salesforce<\/strong><\/a>\u00a0ecosystem. It is deeply integrated\u00a0into Salesforce with an interactive user interface.\u00a0<\/p>\n The cloud analytics platform can analyze data from outside Salesforce as well. Using\u00a0tools\u00a0like MuleSoft and\u00a0APIs,\u00a0you can connect external data\u00a0sources to analyze.\u00a0<\/p>\n Microsoft Power BI is an excellent cloud data analytics platform for non-technical users. It is\u00a0part of\u00a0the\u00a0Microsoft Azure<\/strong><\/a>\u00a0ecosystem and delivered through both\u00a0the\u00a0web and\u00a0mobile applications.\u00a0\u00a0<\/p>\n It is one of the most affordable enterprise\u00a0cloud\u00a0analytics\u00a0platforms\u00a0for the functionality it offers.\u00a0<\/p>\n Tableau is known for its beautiful, interactive interface that helps users explore data dynamically. The platform was\u00a0acquired\u00a0by Salesforce, which is why it smoothly integrates with the CRM for all kinds of analytics needs.\u00a0\u00a0\u00a0<\/p>\n Users can connect Tableau to\u00a0virtually any\u00a0data source, like cloud warehouses, spreadsheets,\u00a0SQL databases<\/strong><\/a>, or APIs.\u00a0<\/p>\n There are still a few businesses out there that\u00a0haven\u2019t\u00a0adopted 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.\u00a0\u00a0\u00a0<\/p>\n However, you need to take this action\u00a0sooner or later. And here are 5 compelling reasons why this decision will pay you in dividends.\u00a0\u00a0<\/p>\n You\u2019ll\u00a0need a lot of cloud-based\u00a0big data analytics<\/strong><\/a>\u00a0in the coming future. Trust us, data volumes and workloads are of Biblical proportions these days with\u00a0Internet of Things<\/strong><\/a>\u00a0(IoT) and smart devices. Only cloud analytics can meet this increasing demand for scalability.\u00a0\u00a0\u00a0<\/p>\n Cloud data analytics gives you the elasticity, to put it in\u00a0layman\u2019s terms, where compute and storage scale automatically to match your needs. If\u00a0you\u2019re\u00a0a business that deals with real-time customer data, shifting to cloud analytics is a matter of ensuring your survival.\u00a0<\/p>\n Adding\u00a0the prefix \u201cAI-powered\u201d to anything is the neologism of our age.\u00a0However,\u00a0actually incorporating\u00a0AI\u00a0solutions<\/strong><\/a>\u00a0into any system is not a piece of cake.\u00a0Data analytics is the same. You would have to hire a team of AI\/ML engineers to make your on-premises infrastructure AI-capable.\u00a0\u00a0<\/p>\n Cloud analytics platforms, on the other hand, come pre-integrated with AI\/ML capabilities such as\u00a0predictive modeling<\/strong><\/a>, generative insights, and natural-language interfaces.\u00a0\u00a0<\/p>\n For example, Oracle Analytics Cloud embeds ML and generative AI capabilities for business users. Users can apply one-click predictive models\u00a0without needing a data scientist.\u00a0<\/p>\n We all have our opinions\u00a0about\u00a0working from home<\/strong><\/a>. Most of our team\u00a0prefer\u00a0the office because\u00a0they find it more productive. But\u00a0remote work is\u00a0now\u00a0part and parcel\u00a0of corporate life. Workforces are now global and mobile, which is why data\u00a0accessibility\u00a0needs to mirror\u00a0this reality.\u00a0\u00a0<\/p>\n Cloud analytics platforms\u00a0allow secure, browser-based access from anywhere to ensure teams can collaborate on live dashboards regardless of location or device.\u00a0Telling from first-hand experience,\u00a0we have distributed teams across the United States, China, and Pakistan. Cloud analytics is critical to our global operations and cross-border setups.\u00a0<\/p>\n Orienting towards cloud analytics\u00a0is ideal for making your organization\u2019s work culture hybrid and\u00a0flexible.\u00a0\u00a0<\/p>\n Upfront investments in traditional analytics can reach millions.\u00a0This is simply out of the equation for\u00a0small and medium enterprises<\/strong><\/a>\u00a0(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\u00a0what\u00a0you\u00a0use,\u00a0which lets you\u00a0scale\u00a0resources up or down dynamically.\u00a0<\/p>\n Furthermore, even big IT corporations are leaning towards\u00a0OPEX models<\/strong><\/a>\u00a0for predictable costs that preserve liquidity.\u00a0If you want to try new datasets without long procurement cycles or the infrastructure overhead,\u00a0cloud analytics should be your top priority going into 2026.\u00a0\u00a0<\/p>\n The Cambridge Dictionary describes the word\u00a0laggard<\/strong><\/a>\u00a0in\u00a0Business\u00a0English\u00a0as\u00a0\u201cA\u00a0company, organization, etc. that does something later, or improves less quickly, than others.\u201d\u00a0Now we\u00a0don\u2019t\u00a0mean to use it in a negative way because we know transitioning to cloud analytics is\u00a0an\u00a0expensive and serious undertaking.\u00a0<\/p>\n However, delaying this transformation is now more expensive than undertaking it.\u00a0Your legacy analytics systems can pile up hidden costs, outdated integrations, and security vulnerabilities.\u00a0\u00a0<\/p>\n Moving to cloud data analytics\u00a0will cost you much less than doing nothing\u00a0in the long run. It also ensures that you\u00a0remain\u00a0relevant and\u00a0toe-to-toe with your competitors in the industry.\u00a0<\/p>\n People think of cloud computing as something intangible, but\u00a0it\u2019s\u00a0really just\u00a0rooms of\u00a0very large\u00a0computers.\u00a0And that is why there are\u00a0different types\u00a0of cloud analytics\u00a0depending on who controls and has access to these data centers.\u00a0\u00a0<\/p>\n Your data and analytics run on shared infrastructure owned by a third-party provider such as AWS, Microsoft Azure, or Oracle Cloud.\u00a0On public clouds, your data is kept private, but IT systems are shared with anyone who uses or\u00a0purchases\u00a0their services.\u00a0<\/p>\n A private cloud is usually behind\u00a0a firewall\u00a0and\u00a0is only\u00a0dedicated to your organization. It is not accessible to the\u00a0general public\u00a0and is\u00a0similar to\u00a0your company\u2019s intranet.\u00a0For example,\u00a0VMware Cloud offers private cloud services where the underlying IT infrastructure is solely dedicated to your enterprise\u00a0with complete isolated access.\u00a0<\/p>\n A\u00a0hybrid\u00a0cloud<\/strong><\/a>\u00a0is a combination of public clouds and private clouds.\u00a0You can use a public cloud for analyzing non-sensitive data and a private cloud to perform cloud analytics on proprietary company data.\u00a0\u00a0<\/p>\n Some companies even mix in on-premises systems for more control and security.\u00a0\u00a0<\/p>\n You need to focus on some key factors while making the move to cloud analytics.\u00a0It will save you a lot of\u00a0trouble\u00a0later on.\u00a0<\/p>\n You\u00a0don\u2019t\u00a0have to move all your data to the cloud to use cloud\u00a0analytics, but the cloud system needs a way to access it, either through integration, a hybrid setup, or a one-time transfer.\u00a0<\/p>\n Whatever you choose, the data needs to be clean and structured.\u00a0If your data is messy or inconsistent, it can cause big downstream problems like duplicate records, reporting errors, or poor decision-making.\u00a0<\/p>\n Use\u00a0data management tools<\/strong><\/a>\u00a0to ensure that\u00a0your\u00a0key\u00a0business data is\u00a0standardized. It will\u00a0greatly improve\u00a0the performance of your cloud analytics tasks.\u00a0\u00a0<\/p>\n Design your cloud analytics environment around\u00a0self-service BI<\/strong><\/a>. And no, it\u00a0doesn\u2019t\u00a0just mean training your employees how to access and use BI tools\u00a0themselves.\u00a0Data analytics in cloud computing is something better.\u00a0\u00a0<\/p>\n Using cloud technology, people can do more on their own without\u00a0IT\u00a0support.\u00a0For example, different team members can access data directly without\u00a0the\u00a0need\u00a0for\u00a0IT helpdesk support.\u00a0\u00a0\u00a0<\/p>\n This kind of self-service saves time, speeds up decisions, and keeps teams focused on insight instead of waiting for\u00a0approvals.\u00a0<\/p>\n When you move to cloud analytics, being open and clear about costs is essential.\u00a0The first cloud bill often takes businesses by surprise. But usually\u00a0it\u2019s\u00a0due to their own doing, like\u00a0someone\u00a0used an expensive storage\u00a0option\u00a0by mistake, or\u00a0didn\u2019t\u00a0scale down resources when usage dropped.\u00a0\u00a0<\/p>\n These small oversights can quickly turn into big surprises on your bill. Therefore, be\u00a0clear about\u00a0what different teams are spending and why.\u00a0It helps people see which parts of the analytics environment are delivering value and which are just draining budgets.\u00a0\u00a0<\/p>\nWhat\u00a0is\u00a0cloud analytics?\u00a0<\/h2>\n
Popular cloud data analytics platforms\u00a0<\/h2>\n
1. SAP Analytics Cloud\u00a0<\/h3>\n
2. Oracle Analytics Cloud\u00a0<\/h3>\n
3. Salesforce Analytics Cloud\u00a0<\/h3>\n
4. Microsoft Power BI\u00a0<\/h3>\n
5. Tableau\u00a0\u00a0<\/h3>\n
5\u00a0benefits of shifting your business to cloud analytics\u00a0<\/h2>\n
1. Scalability\u00a0and agility in the age of IoT\u00a0<\/h3>\n
2. AI-powered analytics\u00a0<\/h3>\n
3. Remote and hybrid work\u00a0<\/h3>\n
4. Cost-effective and efficiency\u00a0<\/h3>\n
5. The cost of stagnation\u00a0<\/h3>\n
Types of cloud analytics\u00a0<\/h2>\n
\n
1. Public\u00a0cloud\u00a0<\/h3>\n
2. Private cloud\u00a0<\/h3>\n
3. Hybrid Cloud\u00a0<\/h3>\n
Best practices to move\u00a0your analytics to the cloud\u00a0<\/h2>\n
1. Structure your data\u00a0<\/h3>\n
2. Emphasize self-service\u00a0<\/h3>\n
3. Be clear about costs\u00a0<\/h3>\n