Normalization
The Normalization processor eliminates redundant data (storing the same data in more than one table) and ensures data dependencies make sense (only storing related data in a table). This processor is also used to eliminate the undesirable characteristics like Insertion, Update and Deletion Anomalies.
- Initially, a window of value is observed, and the next value is converted between 0 and 1, based on the method of normalization used
- Afterwards, the values follow moving window algorithm and the next value is again placed between 0 and 1 based on the previous window
Parameters | Details |
|---|---|
Mode | This parameter determines the form of standardization/normalization to be applied to the data. It allows you to specify the method of normalization to be used, such as Min-Max scaling or Average Standard Deviation. |
Window Size | This parameter specifies the number of values to observe when applying the normalization algorithm. It defines the size of the window used in the moving window algorithm for normalizing the data. |
Note: When creating an analytics flow with Normalization processor, refer the Use the Normalization Processor Function guide for more details.