[amp_mcq option1=”TRUE” option2=”nan” option3=”nan” option4=”nan” correct=”option3″]<\/p>\n
The correct answer is: True.<\/p>\n
Big data veracity is the accuracy, completeness, and timeliness of big data. It is one of the three V’s of big data, along with volume and velocity.<\/p>\n
Big data veracity is important because it affects the quality of the insights that can be derived from big data. If the data is not accurate, complete, or timely, then the insights will be inaccurate, incomplete, or untimely.<\/p>\n
There are a number of challenges to big data veracity. One challenge is that big data is often unstructured, which makes it difficult to clean and validate. Another challenge is that big data is often generated from multiple sources, which can make it difficult to ensure that the data is consistent.<\/p>\n
There are a number of techniques that can be used to improve big data veracity. One technique is to use data quality tools to clean and validate the data. Another technique is to use data integration tools to combine data from multiple sources.<\/p>\n
Big data veracity is an important issue that needs to be addressed in order to derive accurate and timely insights from big data.<\/p>\n
Here is a brief explanation of each option:<\/p>\n
[amp_mcq option1=”TRUE” option2=”nan” option3=”nan” option4=”nan” correct=”option3″]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[734],"tags":[],"class_list":["post-50003","post","type-post","status-publish","format-standard","hentry","category-introduction-to-data-science","no-featured-image-padding"],"yoast_head":"\n