This data transformation process can consist of several tasks that will be used to apply different kinds of data transformations. Essentially this converts raw data to a more focused and meaningful data set. There, the data extracted from various sources and within the staging area (temporary storage) goes through a data processing phase to transform so that they can be used for analytics. This is the transformation stage of the ETL process. In that case, extraction should be carried out by different means, such as a read replica of the production database. For example, assume that extraction from a production database causes adverse performance issues that hinder the overall application performance. In any extraction method, we have to ensure that it will not affect the performance of the underlying system. However, this method should only be used on small datasets as it can be a time-consuming and resource-intensive process. In these instances, the only option is to reload the entire data set.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |