What is Data Veracity?

Written by Caitlin Davidson

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Data Veracity Defined

Data veracity refers to the quality of data that is to be analyzed. The quality of data is dependent on certain factors such as; where the data has been collected from, how it was collected, and how it will be analyzed.

The veracity of a users data, dictates how reliable and significant the data really is. Low veracity data, usually contains a high percentage of non-valuable, ‘noisy’ and meaningless data, that will not benefit an organization’s analysis. High veracity data, on the other hand, contains many records that are valuable to a organization analysis, contributing in a meaningful way to the overall results.

Amassing a lot of data does not mean the data becomes clean and accurate. When collecting data from social media sites, the data should be extracted directly from the social media site, instead of a third-party system, as the quality of the data may be jeopardized.  All data must  remain consolidated, cleansed, consistent, and current for businesses to use the data efficiently to make the right decisions.

Veracity is apart of specific attributes of big data. Other attributes include:

In Data Defined, we help make the complex world of data more accessible by explaining some of the most complex aspects of the field.

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