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Although most data entered into a computer are stored in a database, a significant amount is stored in a spreadsheet. [17] The use of spreadsheets instead of databases for data entry can be traced to the 1979 introduction of Visicalc, [18] and what some consider the wrong place [19] for storing computational data continues.
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 ]
Sourcetable [9] – AI spreadsheet that generates formulas, charts, SQL, and analyzes data. ThinkFree Online Calc – as part of the ThinkFree Office online office suite, using Java; Quadratic - A source available online spreadsheet for technical users, supporting Python, SQL, and Formulas.
Example of a spreadsheet holding data about a group of audio tracks. A spreadsheet is a computer application for computation, organization, analysis and storage of data in tabular form. [1] [2] [3] Spreadsheets were developed as computerized analogs of paper accounting worksheets. [4] The program operates on data entered in cells of a table.
A spreadmart (spreadsheet data mart) is a business data analysis system running on spreadsheets or other desktop databases that is created and maintained by individuals or groups to perform tasks that can be done in a more structured way by a data mart or data warehouse. [1]
They can be missed by editors quite easily, just as they can be created quite easily. The most obvious cure for the errors is for the user to watch the screen when they type, and to proofread. If the entry is occurring in data capture forms, databases or subscription forms, the designer of the forms should use input masks or validation rules.
Data in local databases and spreadsheets can very easily be modified, either intentionally or otherwise. Once changed it can be hard to track what changes have been made and what the original data looked like. Where the system manipulates the data it can introduce more subtle errors that remain completely undetected for long periods.
In the 1970s relational databases as well as spreadsheets appeared. Relational data bases structure data into tables using structured query languages which made them more efficient than the preceding storage solutions, and spreadsheets hold high volumes of numeric data which can be applied to these relational databases to produce derivative data.