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Characteristics That Define Quality Data

Data has nowadays become a major commodity for the enterprises all around the world to scale & grow. Many organizations are spending millions of dollars to acquire data of accuracy & good quality. The crucial challenge here lies in defining what factors represent the quality in the data. Most of the times, Data which is collected could be viewed as of good quality by some people & there would be others who would be viewing the same data as of poor quality.

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Speaking of Data quality, to accurately determine this we need to examine several factors and then weighing those factors according to the requirements of the enterprises.  Now, let’s take a look at different factors that determine the Data Quality.

Accuracy & Precision

These characteristics refer to the exactness of the data. The data collected from various sources shouldn’t be having any sort of erroneous elements & it should accurately address the problem without misleading. To determine the extent of accuracy and precision, it is very much important to understand the need for the data how it is going to be consumed.

Legitimacy & Validity-

These characteristics are generally rely on the requirements that govern the data set. This means that, if a survey is being conducted then items such as gender, ethnicity, linguistic, age limit & such are typically limited to a set of options and open answers are not permitted. So any opinion which is coming from those set of people who doesn’t belong to any of the prescribed set of conditions would simply be termed as in valid.

Availability & Accessibility

Determining these characters would mostly be tricky constraints like legal & regulation issues. Irrespective of these challenges getting the right level of access to collect the data is very crucial to achieve the desired objectives.

Apart from these, the other factors which determine the Data Quality are how reliable & consistent is the Data, Completeness and Comprehensiveness, Data Timeliness & its Relevance, Granularity and Uniqueness.