DZone

According to Gartner’s report, 40% of businesses fail to achieve their business targets because of poor data quality issues. The importance of utilizing high–quality data for data analysis is realized by many data scientists, and so it is reported that they spend about 80% of their time on data cleaning and preparation. This means that they spend more time on pre-analysis processes, rather than focusing on extracting meaningful insights.

Although it is necessary to achieve the golden record before moving on to the data analysis process, there must be a better way of fixing the data quality issues that reside in your dataset, rather than correcting each error manually.

Source: DZone