Question

Data Quality Model

Complete the chart by defining each of the terms you labeled in the diagram and provide a specific example of that characteristic

Term	Definition	Example
A Application	The purpose for the data collection
B Analysis	The process of translating data into meaningful information
C Collection	The processes by which data elements are accumulated
D Warehousing	Processes and systems used to archive data
1 Data Accuracy	The extent to which the data are free of identifiable errors
2 Data Accessibility	The level of ease and efficiency at which data are legally obtainable, within a well protected and controlled environment
3 Data Comprehensiveness	The extent to which all required data within the entire scope are collected, documenting intended exclusions
4 Data Consistency	The extent to which the healthcare data are reliable, identical, and reproducible by different users across applications
5 Data Currency	The extent to which data are up-to-date; a datum value is up-to-date if it is current for a specific point in time, and it is outdated if it was current at a preceding time but incorrect at a later time
6 Data Definition	The specific meaning of a healthcare-related data element
7 Data Granularity	The level of detail at which the attributes and characteristics of data quality in healthcare data are defined
8 Data Precision	The degree to which measures support their purpose, and/or the closeness of two or more measures to each other
9 Data Relevancy	The extent to which healthcare-related data are useful for the purposes for which they were collected
10 Data Timeliness	The availability of up-to-date data within the useful, operative, or indicated time

Answer 1

Term	Definition	Example
A Application	The purpose for the data collection	Expanded information generation by the private segment. Verifiably, large scale manufacturing of geospatial information was the space of administrative offices, for example, the US Environmental Review.
B Analysis	The process of translating data into meaningful information	Expanded utilization of GIS as a choice help device. This pattern has prompted acknowledgment of the potential pernicious impacts of utilizing low quality information, including the likelihood of prosecution if least guidelines of value are not achieved
C Collection	The processes by which data elements are accumulated	Expanded dependence on optional information sources. This has been powered by a decrease in openness and cost requirements coming about because of system availability and the improvement of gauges for information trade
D Warehousing	Processes and systems used to archive data	Until as of late information quality was the duty of the maker, and consistence testing techniques were connected with the end goal to purify databases meeting official quality limits.
1 Data Accuracy	The extent to which the data are free of identifiable errors	Consistence testing is a type of value control that tries to dispose of mistake through administration of the database generation process. However, compliance tests are valuable just in a constrained scope of uses situations.
2 Data Accessibility	The level of ease and efficiency at which data are legally obtainable, within a well-protected and controlled environment	For a few applications a specific consistence test might be excessively careless while for other people, it might be excessively prohibitive and henceforth give pointless expenses.
3 Data Comprehensiveness	The extent to which all required data within the entire scope are collected, documenting intended exclusions	Duty regarding evaluating whether a database addresses the issues of a specific application has in this manner moved to the buyer who is in a situation to make such an appraisal.
4 Data Consistency	The extent to which the healthcare data are reliable, identical, and reproducible by different users across applications	As opposed to delivering definitive databases, the maker's job has moved to information quality documentation or 'truth-in-naming'. Reality in-naming worldview sees blunder as unavoidable and throws the information quality issue as far as abuse emerging from fragmented learning of information restrictions.
5 Data Currency	The extent to which data are up-to-date; a datum value is up-to-date if it is current for a specific point in time, and it is outdated if it was current at a preceding time but incorrect at a later time	Topographical perceptions portray wonders with spatial, fleeting, and topical segments
6 Data Definition	The specific meaning of a healthcare-related data element	Albeit inadequately suited in ordinary geospatial information models, time is basic to a comprehension of geological marvels, not as elements that exist at some area, but rather as occasions that show up and vanish in space and time
7 Data Granularity	The level of detail at which the attributes and characteristics of data quality in healthcare data are defined	A second issue is that land wonders are not by some bounce of the imagination about space, yet about subject.
8 Data Precision	The degree to which measures support their purpose, and/or the closeness of two or more measures to each other	The facts demonstrate that without space there is nothing geological about the information, yet then again without subject there is just geometry.
9 Data Relevancy	The extent to which healthcare-related data are useful for the purposes for which they were collected	Like geological marvels, information quality can be separated in space, time, and subject. For each one of these measurements, a few parts of value (counting exactness, accuracy, consistency, and culmination) can be identified.
10 Data Timeliness	The availability of up-to-date data within the useful, operative, or indicated time	An adjustment in space or time suggests an adjustment in topic, and the other method nearby. In this manner while precision can be estimated independently for space, time, and subject, these estimations are not really free.