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By 03 November 2021
Unlock the hidden potential of your customer and other data
Cloud analytics refers to the use of cloud computing to analyze large amounts of data with the goal of identifying patterns and extracting insights, typically for business use.
Cloud analytics enables businesses to leverage superior computing power from a third-party cloud computing provider without having to invest in expensive infrastructure. Many such providers offer built-in cloud analytics services, while others simply allow businesses to make use of powerful, scalable processing power and storage. In all scenarios, however, there are two main components involved:
By bringing cloud analytics to bear on customer and other data, businesses can gain precious new insights to improve products, services, processes, and policies.
A data center/server farm
Sales and Marketing
Understanding customer behavior is one of the most common uses of cloud analytics for most small and medium-sized businesses (SMB). Customer interactions, whether digital (via a business’ website, mobile app, or desktop application) or physical (when visiting a store or service center), generate huge quantities of data. Businesses that are able to collect and then analyze that data can better understand their customers’ expectations, desires, and frustrations. 
Salesforce is one example of a customer relationship management (CRM) platform that can easily be paired with cloud analytics software like Tableau, enabling sales and marketing teams to reveal hidden trends and insights in their existing and growing data. 
Another business department typically flush with large quantities of data is the finance department. Finance departments are responsible for bookkeeping, managing cash flow, budgets and forecasting, sourcing long-term investments, and managing taxes. These are its day-to-day tasks, but it’s also responsible for analyzing all the financial data generated by the business’ operations and providing reports to guide the decisions of managers and executives. 
Financial cloud analytics solutions like Oracle Cloud include powerful, ready-made algorithms and analytical tools for businesses to use as needed. The raw processing is performed by powerful machines in data centers that have been custom-built to power through billions of data points in mere hours. Thus, even small businesses can gain greater insight from their financial activities.
People with computers sitting around a desk at a meeting
Research and Development (R&D)
For businesses in pharmaceuticals, life sciences, biotech, consumer technology, and more, research and development departments have the important role of discovering innovative new products for consumers. What bridges the gap between the research (data collection) and development (data application) is, of course, analytics. 
Most businesses recognize the value in a dedicated R&D department, but historically the costs prohibited all but the largest from doing so. Cloud analytics platforms allow even small businesses to set up an R&D center that can process huge amounts of data in record time and for little cost. 
Information Technology (IT)
IT departments are well placed to take advantage of cloud analytics. In addition to having the technical expertise, they have multiple means of collecting valuable information on how employees use the various applications and tools at their disposal.
Cloud analytics provide a way for IT departments to organize and understand that data, offering numerous benefits. Trends in application use data may point to potential security threats, for example, or highlight new ways to reduce operational costs.
Analyzing data from the cloud offers businesses a number of advantages.
Cloud analytics, and cloud computing in general, provides greater scalability to businesses, enabling them to increase (or decrease) the level of processing power and storage as necessary. Historically, this couldn’t be done easily, as businesses had to purchase (and sell off) their own machines—a cost-ineffective process. 
As a business’ data analytics needs grow, they need only request additional processing power.
Cloud analytics providers typically offer numerous ways for businesses to analyze their data, with specific algorithms designed to uncover trends in a wide variety of datasets. As a result, businesses can pick and choose the algorithms that matter to them most, without having to worry about the expense of developing them. 
It also dramatically increases the number of questions businesses can ask about their data and thus the insights they can glean. 
Cloud providers offer top-tier infrastructure at a dramatically reduced cost, passing along economies of scale to businesses. Subscription-based models also enable businesses to move from the capital expenses of purchasing costly machines to operational expenses, bringing certain tax and cash flow benefits.
Cloud analytics companies typically offer robust security to meet or exceed on-premises solutions. For example, Amazon Web Services (AWS), a popular cloud computing solution with powerful analytics software, provides a range of security measures including identity and data access management, threat detection, data protection, incidence response, and guaranteed compliance.
Collaboration and connectivity
Cloud platforms tend to allow for greater collaboration, as the data and software are decentralized, easily accessible from a desktop, tablet, or mobile app, and can be used by any number of individuals at once. 
Additionally, modern cloud analytics solutions usually offer a variety of integrations—seamless connections to third-party software your business may already be using, including CRM like Salesforce and financial suites like Freshbooks or Quickbooks.
Two people collaborating with their computers and paper
Like cloud computing more generally, cloud analytics solutions vary widely in cost, although cloud analytics giants like Google Cloud and Amazon Web Services offer very cost-effective packages for businesses of all sizes. Typically, you’ll only pay for processing power and operations as you use them. 
For example, Google’s Big Query costs $5.00 per terabyte (TB) of data read from your database, with the first 1TB per month free. Its Dataflow analytics software is priced per “dataflow processing unit,” which roughly translates to the number of operations run per hour, starting at $0.071 per DSU per hour. You can take advantage of Google’s pricing calculator for a better idea of your monthly costs. 
Many small analytics companies offer simple subscriptions. SAP Analytics Cloud, for example, has a Business Intelligence plan for $36/mo. It includes a variety of data connections, pre-built data modeling, discovery and exploration, advanced analytics, live data connectivity, and more. 
Small businesses with lighter analytics needs can expect to pay anywhere from $30 to $80 per month. Enterprise companies requiring advanced, data-heavy, power-hungry analytics may pay thousands, even tens of thousands of dollars per month.
Man standing in front of an Amazon Web Services sign
Frequently asked questions about cloud analytics.
There are many advantages to doing your business analytics in the cloud. It’s typically cheaper than acquiring on-premises infrastructure, with more flexible pricing. Security is superior and built-in, and you can rapidly scale up or down as necessary. 
Cloud analytics providers also offer a wide range of analytics and algorithms, plus customer and technical service agents to help you make the most of your data.
There is no “best cloud” for data analytics, although there are some that stand out. Microsoft Azure, Amazon Web Services, and Google Cloud are all cloud computing heavy-hitters that offer cost-effective analytics solutions. The level of processing power, cloud storage, and diverse analytics and algorithms available to businesses is unmatched, making these an excellent choice for most companies. 
Big data refers to the particularly large amounts of data collected by many businesses, typically to understand customer behavior. Like “Big Pharma,” it can also mean companies whose business model is based on collecting, analyzing, and exploiting such data, like Facebook and Google. 
The key objective of data analytics is to uncover patterns and trends in data, which can then be used to learn more about the world, inform decision-making processes, and drive policies. 
It hinges on the assumption that data is structured, not random, and that with sufficient processing power, that structure can be understood and exploited.
Beyond cloud analytics, there are a number of reasons for businesses to switch to cloud computing. The best cloud computing services offer cost-effective ways to store, manipulate and analyze data, plus a variety of other tools such as IaaS, PaaS and SaaS.
Christian is a freelance writer and content project manager, with over six years’ experience writing and leading teams in finance and technology for some of the world’s largest online publishers, including TechRadar and Tom’s Guide. 
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