Truth be told, there’s no way data processing and analysis can take place without data profiling. As data gets bigger and infrastructure moves to the cloud, data profiling is becoming more important than ever. Just in case you did not know, data profiling involves reviewing source data, understanding structure and determining potential for data projects.
For you to get the most from data profiling you ought to know the different types that exist. Luckily, we are here to offer a helping hand. Here are the three main types of data profiling you ought to know about.
Structure discovery makes it easy for organizations to figure out how well data is structured. For instance, you can go through phone numbers and determine the percentage that does not have the correct number of digits. Keep in mind validating data is all about making it consistent and ensuring it’s in the correct format. Through this action, you’ll certainly have an easy time when performing mathematical checking on the data.
Content discovery is all about examining the individual data records with the main intention of discovering the errors present. Provided it is carried out in the best possible manner, content discovery will help you identify the specific rows in a table containing issues. If this is not enough, you can figure out the systemic problems that occur in the data.
Last but not least is relationship discovery which entails figuring out the interrelationship that exists between parts of the data. For instance, you can figure out the relationship between cells or tables in a spreadsheet. By understanding the relationships, you’ll be able to reuse the data. It is highly advisable for you to unite related data sources into one or simply import it in a way that keeps important relationships.
The Bottom Line
These are the three types of data profiling you need to be fully aware of. Be sure to carry out a detailed research if you are to figure out what they entail before making any decision.