Ad
related to: 6 dimensions of data quality pdf
Search results
Results From The WOW.Com Content Network
Data quality assurance is the process of data profiling to discover inconsistencies and other anomalies in the data, as well as performing data cleansing [17] [18] activities (e.g. removing outliers, missing data interpolation) to improve the data quality.
ISO 8000 is the international standard for Data Quality and Enterprise Master Data.Widely adopted internationally [1] [2] [3] it describes the features and defines the requirements for standard exchange of Master Data among business partners.
Larry English prefers the term "characteristics" to dimensions. [6] In fact, a considerable amount of information quality research involves investigating and describing various categories of desirable attributes (or dimensions) of data. Research has recently shown the huge diversity of terms and classification structures used. [7]
Within systems engineering, quality attributes are realized non-functional requirements used to evaluate the performance of a system. These are sometimes named architecture characteristics, or "ilities" after the suffix many of the words share.
[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. Common tasks include record matching, identifying inaccuracy of data, overall quality of existing data, deduplication, and column segmentation. [23]
See also: category:Data security (data loss prevention is in fact an assurance of data quality) Subcategories This category has the following 2 subcategories, out of 2 total.
While data governance initiatives can be driven by a desire to improve data quality, they are often driven by C-level leaders responding to external regulations. In a recent report conducted by CIO WaterCooler community, 54% stated the key driver was efficiencies in processes; 39% - regulatory requirements; and only 7% customer service. [6]
The Information Quality Act (IQA) or Data Quality Act (DQA), passed through the United States Congress in Section 515 of the Consolidated Appropriations Act, 2001 (Pub. L. 106–554 (text)). Because the Act was a two-sentence rider in a spending bill , it had no name given in the actual legislation.