Search results
Results from the WOW.Com Content Network
Data cleansing may also involve harmonization (or normalization) of data, which is the process of bringing together data of "varying file formats, naming conventions, and columns", [2] and transforming it into one cohesive data set; a simple example is the expansion of abbreviations ("st, rd, etc." to "street, road, etcetera").
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.
SAS data can be published in HTML, PDF, Excel, RTF and other formats using the Output Delivery System, which was first introduced in 2007. [9] SAS Enterprise Guide is SAS's point-and-click interface. It generates code to manipulate data or perform analysis without the use of the SAS programming language.
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).
The additional data can simply be a complete copy of the actual data (a type of repetition code), or only select pieces of data that allow detection of errors and reconstruction of lost or damaged data up to a certain level.
The ORDER BY clause identifies which columns to use to sort the resulting data, and in which direction to sort them (ascending or descending). Without an ORDER BY clause, the order of rows returned by an SQL query is undefined. The DISTINCT keyword [5] eliminates duplicate data. [6] The following example of a SELECT query returns a list of ...
SAS Institute (or SAS, pronounced "sass") is an American multinational developer of analytics and artificial intelligence software based in Cary, North Carolina. SAS develops and markets a suite of analytics software ( also called SAS ), which helps access, manage, analyze and report on data to aid in decision-making.
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.