Chapter 4. Data Validation and Cleansing Patterns
In the previous chapter, you have studied the various patterns related to data profiling, through which you understood the different ways to get vital information about the attributes, content, context, structure, and condition of data residing in the Hadoop cluster. These data profiling patterns are applied in the data lifecycle before initiating the process of cleaning the data into a more useful form.
The following are the design patterns covered in this chapter:
- Constraint validation and cleansing pattern: This explains the validation of the data against a set of constraints to check if there are any missing values, if the values are within a range specified by a business rule or if the values ...
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