Data Quality and data integrity are both important aspects of data analytics. With the rapid development of data analytics, data can be considered one of the most important assets a business owns. As a result, many organizations collect massive amounts of data for research and marketing purposes.
However, the value of this data depends on its usability and accuracy. Because data comes from a variety of sources, often with different formatting, and can be stored multiple times – with some copies containing errors – working with large quantities of data can become difficult.
