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Data analysis is the process of inspecting, cleansing, transforming, and modeling data with the goal of discovering useful information, informing conclusions, and supporting decision-making. [1]
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.
Software analytics is the analytics specific to the domain of software systems taking into account source code, static and dynamic characteristics (e.g., software metrics) as well as related processes of their development and evolution.
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."
SAS (previously "Statistical Analysis System") [1] is a statistical software suite developed by SAS Institute for data management, advanced analytics, multivariate analysis, business intelligence, criminal investigation, [2] and predictive analytics. SAS' analytical software is built upon artificial intelligence and utilizes machine learning ...
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 .
Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5] It uses techniques and theories drawn from many fields within the context of mathematics , statistics, computer science , information science , and domain knowledge . [ 6 ]
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).