Cloud analytics describes the application of analytic algorithms in the cloud against data in a private or public cloud to then deliver a result of interest. Cloud analytics involves deployment of scalable cloud computing with powerful analytic software to identify patterns in data and to extract new insights. More and more businesses rely on data analysis to gain a competitive advantage, to advance scientific discovery, or to improve life in all sorts of ways. Data analytics has therefore become an increasingly valuable tool as the quantity and the value of data continue to climb.
Cloud analytics is often associated with artificial intelligence (AI), machine learning (ML), and deep learning (DL). And it is commonly used in industry applications such as scientific research in genomics or in oil and gas fields, business intelligence, security, Internet of Things (IoT), and many others. In fact, any industry can benefit from data analytics to improve organizational performance and to drive new value.
By leveraging AI and other analytics approaches, organizations of all sizes can quickly make data-driven decisions to gain efficiencies in their products and services. The cloud is an indispensable platform that enables quick experimentation of ideas through proofs of concept (POCs) and provides a rich software ecosystem for building AI applications and for training DL models.
AI is increasingly being used in multiple industry verticals to support important business needs such as automating business processes, providing cognitive insights through data analysis, and interacting with customers with natural language processing. DL, the next level of ML, is effective at learning from large volumes of data to mimic the human brain’s pattern recognition (for example, images, speech, and text).
Cloud infrastructure analytics, a subset of cloud analytics, focuses on the analysis of data that’s associated with IT infrastructure, on the premises or in the cloud. The goal is to identify I/O patterns, to evaluate application performance, to identify policy compliance, and to support capacity management and infrastructure resilience.