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Data mining is a particular data analysis technique that focuses on statistical modeling and knowledge discovery for predictive rather than purely descriptive purposes, while business intelligence covers data analysis that relies heavily on aggregation, focusing mainly on business information. [4]
Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.
[1]--- centers on analytics applied to artifacts a software system is composed of. "Software analytics is analytics on software data for managers and software engineers with the aim of empowering software development individuals and teams to gain and share insight form their data to make better decisions."
Communication software is used to provide remote access to systems and exchange files and messages in text, audio and/or video formats between different computers or users. This includes terminal emulators , file transfer programs, chat and instant messaging programs, as well as similar functionality integrated within MUDs .
Silver et al. (1995) provided two views on IS that includes software, hardware, data, people, and procedures. [23]The Association for Computing Machinery defines "Information systems specialists [as] focus[ing] on integrating information technology solutions and business processes to meet the information needs of businesses and other enterprises."
The Software Communications Architecture (SCA) is an open architecture framework that defines a standard way for radios to instantiate, configure, and manage waveform applications running on their platform. The SCA separates waveform software from the underlying hardware platform, facilitating waveform software portability and re-use to avoid ...
reading data from a nominated operational system (ERP, CRM, SCM, etc.) into a data warehouse optimized for analysis (data led automation), reports, dashboards and scorecards based on that data structure (reporting led automation), what-if analysis and scenario-modeling (predictive or analytic led automation).
An email management system consists of various components to handle different phases of the email management process. [15] These components include: Email ticketing system - One of the key tasks performed by email management systems is to allocate reference numbers to all incoming emails. This process is known as ticketing.