Ads
related to: data science ppt free downloadaippt.com has been visited by 100K+ users in the past month
Search results
Results From The WOW.Com Content Network
Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4] Data science is "a concept to unify statistics, data analysis, informatics, and their related methods" to "understand and analyze actual phenomena" with data. [5]
Data science process flowchart. John W. Tukey wrote the book Exploratory Data Analysis in 1977. [6] Tukey held that too much emphasis in statistics was placed on statistical hypothesis testing (confirmatory data analysis); more emphasis needed to be placed on using data to suggest hypotheses to test.
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 ]
In computer science, an array is a data structure consisting of a collection of elements (values or variables), of same memory size, each identified by at least one array index or key. An array is stored such that the position of each element can be computed from its index tuple by a mathematical formula.
Data profiling is the process of examining the data available from an existing information source (e.g. a database or a file) and collecting statistics or informative summaries about that data. [1] The purpose of these statistics may be to: Find out whether existing data can be easily used for other purposes
SlideShare is an American hosting service, now owned by Scribd, for professional content including presentations, infographics, documents, and videos.Users can upload files privately or publicly in PowerPoint, Word, or PDF format.
Data analysis uses specialized algorithms and statistical calculations that are less often observed in a typical general business environment. For data analysis, software suites like SPSS or SAS, or their free counterparts such as DAP, gretl, or PSPP are often used. These tools are usually helpful for processing various huge data sets, as they ...
A semantic data model can be used to serve many purposes. Some key objectives include: [1] Planning of data resources: A preliminary data model can be used to provide an overall view of the data required to run an enterprise. The model can then be analyzed to identify and scope projects to build shared data resources.