Normal No Spacing Heading 1 or Updates. Chapter 6- Transforming Data Name: Match the following terms with the appropriate definition or example: aggregate data a process of analyzing data to make certain the data has the properties of high-quality data: accuracy, completeness, consistency, timeliness, and validity. 2 cryptic data values b data values that are correctly formatted but not listed in the correct field. 3 data cleaning C all types of errors that come from inputting data incorrectly. 4 data concatenation d examining data using human vision to see if there are problems. 5 data consistency e the process of tracing extracted or transformed values back to their original source. 6 data contradiction errors f data items that have no meaning without understanding a coding scheme. 7 data de-duplication g the process of changing data into a common format so that is useful for decision-making. data entry errors h a technique that rotates data from a state of rows to a state of columns. 9 data filtering errors that occur when a secondary attribute in a row of data does not match the primary attribute. 10 data imputation a data field that contains only two responses, typically a 0 or 1. Also called a dichotomous variable. 11 data parsing k the principle that every value in a field should be stored in the same way. 12 data pivoting 1 the process of changing the organization and relationships among data fields to prepare the data for analysis. 13 data standardization m data errors that occur when a data value falls outside an allowable level. 14 data structuring a data field that contains only two responses, typically a 0 or 1. Also called a dummy variable. 15 data threshold violations 0 the process of updating data to be consistent, accurate and complete. 16 data validation data that is inconsistent, inaccurate, or incomplete. 17 dichotomous variable separating data combined in a single field into multiple fields. 18 dirty data the combining of data from two or more fields into a single field. 19 dummy variable S the process of replacing a null or missing value with a substituted value. 20 misfielfed data values t the process of removing records or fields of information from a data source. 21 violated attribute u the process of analyzing data and removing two or dependencies more records that contain identical information. 22 visual inspection V the presentation of data in a summarized form. W an error that exists when the same entity is described in two conflicting ways. X the process of ordering data to reveal unexpected values