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XML for Analysis (XMLA) is an industry standard for data access in analytical systems, such as online analytical processing (OLAP) and data mining. XMLA is based on other industry standards such as XML, SOAP and HTTP. XMLA is maintained by XMLA Council with Microsoft, Hyperion and SAS Institute being the XMLA Council founder members.
A review and critique of data mining process models in 2009 called the CRISP-DM the "de facto standard for developing data mining and knowledge discovery projects." [16] Other reviews of CRISP-DM and data mining process models include Kurgan and Musilek's 2006 review, [8] and Azevedo and Santos' 2008 comparison of CRISP-DM and SEMMA. [9]
The National Standardization Agency Organization consists of the Chairman, Main Secretariat, Deputy for Standards Development, Deputy for Application of Standards and Conformity Assessment, Deputy for Accreditation, Deputy for National Standards for Measuring Units, Inspectorates, Research and Development Center for Human Resources, and Data ...
Standardization (American English) or standardisation (British English) is the process of implementing and developing technical standards based on the consensus of different parties that include firms, users, interest groups, standards organizations and governments. [1]
exclusive decision and merging. both data-based and event-based. data-based can be shown with or without the "x" marker. inclusive decision and merging. complex – complex conditions and situations. parallel forking and joining. exclusive decision and merging. both data-based and event-based. exclusive can be shown with or without the "x" marker.
The International Organization for Standardization (ISO / ˈ aɪ s oʊ /; [3] French: Organisation internationale de normalisation; Russian: Международная организация по стандартизации) is an independent, non-governmental, international standard development organization composed of representatives from the national standards organizations of member ...
Process mining is a family of techniques for analyzing event data to understand and improve operational processes. Part of the fields of data science and process management, process mining is generally built on logs that contain case id, a unique identifier for a particular process instance; an activity, a description of the event that is occurring; a timestamp; and sometimes other information ...
Tukey defined data analysis in 1961 as: "Procedures for analyzing data, techniques for interpreting the results of such procedures, ways of planning the gathering of data to make its analysis easier, more precise or more accurate, and all the machinery and results of (mathematical) statistics which apply to analyzing data." [3]