Data Quality

Data Quality

The importance of data quality in the statistical work stems from the importance of the use of statistical data in various fields and wide through studies and research. Therefore, the need to focus on quality control in the production of the statistical number has emerged from many sources. However, despite the divergence of views, there are some criteria and dimensions that must be taken into account when producing the statistical figure.

Although there are many statistical studies and studies that look at the quality of data, there is no clear and specific concept. In any case, they all refer to a scale based on preference of statistical data compared to other statistical products and services. Data in the statistical work refers to all areas and aspects related to the extent to which these data meet the user’s need and responsiveness to his expectations in terms of performance, level, form and content, in addition to the high degree of accuracy of information in all stages and in line with the requirements of users of the statement Decision makers. Data quality is defined by the European Statistics Office as a set of attributes and attributes in a statistical product or service that meets the user’s needs and satisfies its satisfaction. The International Monetary Fund (IMF) defines data quality within the overall DQAF framework within a number of dimensions and levels required to achieve data quality.

Note: All models used in the quality of statistical data applied in the Department of Statistics are periodic throughout the year.

Data Quality Guide

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