Itqualityassurance
- What are data quality challenges?
- What is the main cause of poor data quality?
- Why is data quality a challenge for IT departments?
- What can affect data quality?
What are data quality challenges?
Data quality issues can stem from duplicate data, unstructured data, incomplete data, different data formats, or the difficulty accessing the data. In this article, we will discuss the most common quality issues with data and how to overcome these.
What is the main cause of poor data quality?
Manual data entry errors
Humans are prone to making errors, and even a small data set that includes data entered manually by humans is likely to contain mistakes. Data entry errors such as typos, data entered in the wrong field, missed entries, and so on are virtually inevitable.
Why is data quality a challenge for IT departments?
Data quality challenges pose a threat to organizations' decision-making. Inaccurate, inconsistent, missing and duplicate data poses threats to cultivating trustworthy data sets.
What can affect data quality?
There are five traits that you'll find within data quality: accuracy, completeness, reliability, relevance, and timeliness – read on to learn more. Is the information correct in every detail? How comprehensive is the information? Does the information contradict other trusted resources?
