Data cleansing - Wikipedia
Data cleansing or data cleaning is the process of identifying and correcting (or removing) corrupt, inaccurate, or irrelevant records from a dataset, table, or database. It involves detecting incomplete, incorrect, or inaccurate parts of the data and then replacing, modifying, or deleting the affected data.[1] Data cleansing can be performed interactively using data wrangling tools, or through bat
Data mining - Wikipedia
Data mining is the process of extracting and finding patterns in massive data sets involving methods at the intersection of machine learning, statistics, and database systems.[1] Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal of extracting information (with intelligent methods) from a data set and transforming the information into a comprehensi
Data and information visualization - Wikipedia
Data and information visualization (data viz/vis or info viz/vis) is the practice of designing and creating graphic or visual representations of[2] quantitative and qualitative data and information with the help of static, dynamic or interactive visual items. These visualizations are intended to help a target audience visually explore and discover, quickly understand, interpret and gain important
Raw data - Wikipedia
"Primary data" redirects here. For data that has been created at the time under study, see Primary source. This article needs additional citations for verification. Please help improve this article by adding citations to reliable sources. Unsourced material may be challenged and removed. Find sources: "Raw data" – news · newspapers · books · scholar · JSTOR (December 2009) (Learn how and when to r
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Secondary data - Wikipedia
