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The process can be performed based on algorithms or programmed loops. Trying to match sets of data against each other or comparing complex data types. Data matching is used to remove duplicate records and identify links between two data sets for marketing, security or other uses. [3] Sounds like Function is used to find values that sound similar.
The reasons for this are two-fold: First, data deduplication requires overhead to discover and remove the duplicate data. In primary storage systems, this overhead may impact performance. The second reason why deduplication is applied to secondary data, is that secondary data tends to have more duplicate data.
Displaying the differences between two or more sets of data, file comparison tools can make computing simpler, and more efficient by focusing on new data and ignoring what did not change. Generically known as a diff [1] after the Unix diff utility, there are a range of ways to compare data sources and display the results.
Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).
Once processed and organized, the data may be incomplete, contain duplicates, or contain errors. [21] [22] The need for data cleaning will arise from problems in the way that the datum are entered and stored. [21] Data cleaning is the process of preventing and correcting these errors.
A workbook is physically represented by a file containing all the data for the book, the sheets, and the cells with the sheets. Worksheets are normally represented by tabs that flip between pages, each one containing one of the sheets, although Numbers changes this model significantly. Cells in a multi-sheet book add the sheet name to their ...
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[citation needed] It is a database with the software to validate and manage the data, and keep it synchronized with the systems that use the data. [2] The master data hub has to extract the data from the source system, validate, sanitize and shape the data, remove duplicates, and update the hub repositories, as well as synchronize the external ...