In the data warehousing process, the data staging area is collected of the data staging server software and the data store archive (repository) of the results of extraction, transformation, and loading activity.
The data staging software server temporarily saves and changes data extracted from OLTP data sources and the archival repository stores cleaned, transformed data and attributes for loading into data marts and data warehouses.
The data staging process imports information either as streams or files, change it, produces integrated, cleaned data, and stages it for loading into data warehouses, data marts, or Operational Data Stores.
A data staging tool is accessible, and the data is in a database. The data flow starts so that it appears out of the source system, changes through the transformation engine, and into a staging database.
In the second method, it can start with a mainframe legacy system and then extract the sought-after records into a flat file, change the file to a staging server, transform its contents, and load transformed information into the staging database.
The data warehouse staging area is a temporary area where data from source systems is reproduced. A staging area is generally needed in a Data Warehousing Architecture for timing reasons. Briefly, all required information should be available before data can be unified into the Data Warehouse.
Because of varying business cycles, data processing cycles, hardware, and network resource limitations, and geographical elements, it is not applicable to extract all the information from all Operational databases at accurately the same time.
Example − It can be reasonable to extract sales data daily, but, daily extracts cannot be suitable for financial information that needed a month-end reconciliation procedure. Similarly, it can be suitable to extract “customer” data from a database in Singapore at noon eastern standard time, but this cannot be suitable for “customer” data in a Chicago database.
Data in the Data Warehouse can be persistent (i.e. remains around for a long period) or transitory (i.e. only remains around temporarily). It is not all businesses needed a data warehouse staging area. For many businesses, it is suitable to use ETL to copy data directly from operational databases into the Data Warehouse.
Advantages and Disadvantages of Data Staging
Advantages
The staging process is controlled in parallel with the transformation process.
The disk I/O is decreased in half because the staging table is only written to, against written to, and then extracted from again.
Disadvantages
If the transformation process decline, thus the staging process will also stop.