What is cloud analytics?

Cloud analytics refers to a type of data analysis that shifts elements of data analytics, such as data processing and storage operations, to a public or private cloud. Similar to on-premises data analytics, cloud analytics solutions help you identify patterns, make predictions, and derive business intelligence (BI) insights. However, it extends those capabilities to enable you to work with massive amounts of complex business data using algorithms and cloud technologies. In particular, this type of analysis is often associated with artificial intelligence (AI), such as machine learning (ML) and deep learning (DL) models.

Cloud analytics in cloud computing deliver many of the same capabilities as traditional data analytics. However, rather than hosting everything on-premises, cloud analytics provides the components to support building, deploying, scaling, and managing data analytics in the cloud on a third party’s infrastructure.

Examples of cloud analytics solutions include cloud enterprise data warehouses, data lakes, and on-demand BI and marketing analytics.

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How do cloud analytics work?

Cloud analytics works similarly to other types of cloud computing, providing scalable cloud resources and powerful analytical tools in a public or private cloud. You can access services and solutions as needed under subscription-based or pay-as-you-go pricing.

Typically, the cloud analytics provider manages and maintains the application or service, allowing you to focus more on generating insights without worrying about scaling, performance, or reliability. You can move all aspects of the data analytics process into the cloud or adopt a hybrid model, where certain elements are moved to the cloud to lower costs or improve performance while the rest remain on-premises.

For example, you might use a cloud enterprise data warehouse to store massive amounts of business data pulled from various data sources, including on-premises and cloud-based data sources and business applications. From there, you can use cloud analytics tools to carry out a variety of data analytics use cases, such as cloud reporting, streaming analytics, predictive analytics, machine learning, or embedding analytics and dashboards into other applications and systems.

Types of cloud analytics

Depending on the environment you choose, there are three primary types of cloud analytics in cloud computing: public cloud, private cloud, and hybrid cloud.

Public cloud analytics are offered in a public cloud on multitenant architecture, meaning that multiple organizations can use the same resources and services, such as virtual machines, data storage, and data processing, without sharing data.

Private cloud analytics are accessed by a single organization in a private cloud. Private clouds offer many of the same advantages as a public cloud, but are located in an on-premises data center or hosted offsite on dedicated servers on third-party IT infrastructure. Private cloud analytics solutions benefit from greater data security and privacy. However, they are much more expensive to scale and maintain.

Hybrid cloud analytics combine public and private cloud analytics in a hybrid cloud environment, where you use the public cloud for processing and storing non-sensitive data and use on-premises systems or a private cloud for a smaller amount of sensitive data with stricter governance or data sovereignty requirements. Hybrid cloud analytics deliver analytics capabilities to wherever your data lives, whether in a public cloud, private cloud, or on-premises.

Increasingly, multicloud analytics have become commonplace as more organizations opt to store data in multiple public clouds. Multicloud analytics solutions let you gain insights across all your data wherever it resides, allowing you to access and analyze it without having to move or copy it.

Cloud analytics features and capabilities

You’re using cloud analytics if you have at least one or more critical elements of the data analytics process in the cloud. As previously defined by Gartner, these elements include data sources, data models, data processing, computing power, data storage, and analytic models.

When considering solutions and tools, look for the following cloud analytics features and capabilities that provide one or more of the following:

Data sources: The ability to capture and ingest data or events from many different types of data sources, including websites, ERP and CRM systems, mobile apps, social media platforms, and more. One of the biggest advantages of cloud analytics is real-time data integration, so you can consolidate structured, unstructured, batch, and streaming data without adding a lot of extra complexity.

Data models: Cloud-based data models determine data structure and how data elements relate to each other. Cloud providers should offer cloud analytics solutions that have data models that match your organization's data and specific business requirements.

Data processing: Cloud analytics should offer data processing applications and capabilities for handling large volumes of data coming in from different systems to speed up the time it takes for you to analyze and generate insights.

Computing power: With cloud analytics, data processing requires huge amounts of raw computing power so you can ingest, structure, process, store, and analyze large datasets at scale. Leveraging public cloud resources helps ensure data can be processed and delivered quickly without having to worry about scaling capacity or other provisioning concerns.

Storage and warehousing: In most cases, cloud analytics solves many of the problems of storing and maintaining data stores. Ideally, a cloud analytics solution should offer affordable cloud storage along with other services like a data warehouse that make it easy to access, share, and deliver data to multiple platforms.

Analytics models: Cloud analytics should allow you to leverage pre-built advanced analytics and AI/ML models and develop your own for analyzing complex data to improve real-time predictions, forecasting, and decision-making.

Benefits of cloud analytics

There are many advantages of cloud analytics that can help your organization become more data-driven and improve how you operate. Below are some of the main benefits of cloud analytics:

Consolidated data

Cloud analytics makes it easier to gain a unified view, bringing together all your disparate data sources from different business systems in one place.

Scalability

Cloud analytics leverage on-demand computing resources that allow you to scale storage or analytics capacity up or down to offer quick access to data and to make more informed decisions faster

Easy access

Most cloud analytics solutions offer self-service and easy access to data so data professionals and other business users can analyze and gain deep insights without expert knowledge.

Support for hybrid work

Cloud-based analytics make it easier for employees, partners, and customers to get access to detailed analytics from anywhere and on any device. Files and reports can be shared quickly, increasing collaboration and helping people work together in real time.

Lower costs

On-premises analytics solutions are expensive to purchase, manage, maintain, and extend. With cloud analytics, you can deploy the exact amount of compute and storage required and only pay for what you use. You can also automatically scale up or down if your needs change.

Improved security

Leading cloud providers provide robust security measures and data encryption to ensure the highest levels of security. They also offer advance features for data access, compliance and governance, disaster recovery, and security monitoring to keep data secure.

Cloud analytics use cases

Cloud analytics offer many benefits to your business, from making faster and more accurate decisions to combining more data to get more visibility into what’s happening, to developing prediction models with real-time data.

For example, cloud-based solutions are implemented for many types of analytics, such as website traffic and sales, marketing and social media platforms, financial services, and operational performance. The ability to access and activate data immediately helps you make better decisions in the moment and visualize how different strategies and tactics are performing.

Another common use for cloud analytics is modernizing enterprise data warehouses and data lakes. This allows you to collect, integrate, and analyze data as it’s generated to improve business intelligence while also reducing the time and costs associated with providing data insights.

Cloud analytics helps to enable a rich set of use cases, such as:

Creating unified analytics platforms to build a single source of truth
Build experience management data warehouses to improve experiences and services for customers, employees, and vendors
Identifying new audiences and identifying new potential customers using customer data
Optimizing prices based on dynamic market conditions
Forecasting demand, propensity to purchase, and overall customer lifetime value
Accelerating data analysis of genomic data to improve medical and life sciences research and development
Analyzing infrastructure and cloud usage to improve performance and optimize cloud or IT costs

Learn more about how you can use smart cloud analytics solutions to fuel data-driven transformation and innovation.