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Analytics capability refers to the tools available for key users of IT and OT to analyze and act on the data that is obtained to manage the compute environment. Analytics is reviewed for five types of capabilities, as the following figure shows.
Descriptive analytics is the ability to interpret historical data to understand facility incidents and occurrences. The data provides insights into KPIs related to applications, servers, gateways, security, and network connectivity.
Diagnostic analytics is the ability to interpret historical data to find the root causes of a problem. The data is used to identify causes for downtimes, operational inefficiencies, and security breaches.
Predictive analytics is the ability to interpret historical data to forecast the future occurrence of an event or an incident. It is used to predict events such as server overhead, application failures, and loss of network connectivity to alert key IT users.
Prescriptive analytics is the ability to provide users with the best options to address an intended outcome. It is used for addressing the reliability, performance, and the life cycle management of edge compute environment consisting of servers, applications, and network infrastructure.
Augmented analytics is the ability to augment the stakeholder experience when they are monitoring edge compute environment and analyzing data in real time to identify causes for failure events or incidents. Concepts such as natural language processing (NLP) and machine learning (ML) are leveraged to boost the user experience. This capability also includes predictive analytics capabilities.