Information is interpreted data. Data gives you the 'raw materials' that you process (interpret) and obtain information.
Data is raw facts which are unprocessed or meaningless quantity which is not useful.After making it useful or meaningful it becomes information
2 reasons: - To obtain more free spaces. - To remove away unwanted data & information.
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The more data you have, the more accurate your information. If you have a large amount of evidence of one result, it makes it look correct.
Data collection is a term used to describe a process of preparing and collecting data, for example, as part of a process improvement or similar project. The purpose of data collection is to obtain information to keep on record, to make decisions about important issues, or to pass information on to others. Data are primarily collected to provide information regarding a specific topic.
Data mining is the application of computational techniques to obtain useful information from a large data. When applied to different situations data mining can reveal information and valuable insights about patterns. Examples of data mining applications are Fraud detection, customer behaviour, customer retention.
The Data Management Association has a large variety of tools and resources that allows you to educate yourself in data management. You may also visit the library and check out books.
You calculate summary statistics: measures of the central tendency and dispersion (spread). The precise statistics would depend on the nature of the data set.
educational edge, a small company with limited resources, is interested in segmenting potential markets for its erasable transparencies, what type of data would be best suited to obtain the reguired information?
Data processing involves activities such as cleaning, transforming, organizing, and analyzing raw data to extract valuable insights and information. These processes can include data mining, statistical analysis, visualization, and machine learning techniques to uncover patterns, trends, and relationships within the data.
To get a visual representation of things and to take the data you have and obtain information from the graph about values you have not measured.