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business dashboards; analytic applications; It may extend further to predictive analytics, or predictive analysis may form part of the analytic application - depending on both the subject matter under analysis, and the nature of the analysis required. Analytic applications are typically described as a subset of performance management.
An application analyst (also applications systems analyst) is someone whose job is to support a given application or applications. This may entail some computer programming, some system administration skills, and the ability to analyze a given problem, diagnose it and find its root cause, and then either solve it or pass the problem on to the relevant people if it does not lie within the ...
IT Application Portfolio Management (APM) is a practice that has emerged in mid to large-size information technology (IT) organizations since the mid-1990s. [1] Application Portfolio Management attempts to use the lessons of financial portfolio management to justify and measure the financial benefits of each application in comparison to the costs of the application's maintenance and operations.
In healthcare, business analysis can be used to operate and manage clinical information systems. It can transform medical data from a bewildering array of analytical methods into useful information. Data analysis can also be used to generate contemporary reporting systems which include the patient's latest key indicators, historical trends and ...
A common application of business analytics is portfolio analysis. In this, a bank or lending agency has a collection of accounts of varying value and risk. The accounts may differ by the social status (wealthy, middle-class, poor, etc.) of the holder, the geographical location, its net value, and many other factors.
Object-oriented analysis and design (OOAD) is a technical approach for analyzing and designing an application, system, or business by applying object-oriented programming, as well as using visual modeling throughout the software development process to guide stakeholder communication and product quality.
Generative business intelligence is the application of generative AI techniques, such as large language models, in business intelligence. This combination facilitates data analysis and enables users to interact with data more intuitively, generating actionable insights through natural language queries.
For example, if there are 200 to 300 unique page definitions for a given application, group them into 8–12 high-level categories. This allows for meaningful SLA reports, and provides trending information on application performance from a business perspective: start with broad categories and refine them over time.