. Level of detail: The OLTP layer stores data with a very high level of detail, whereas data in the Data Warehouse is compressed for high-performance access (aggregation).
. History: Archiving data in the OLTP area means it is stored with minimal history. The Data Warehouse area requires comprehensive historical data.
. Changeability: Frequent data changes are a feature of the operative area, while in the Data Warehouse, the data is frozen after a certain point for analysis.
. Integration: In contrast to the OLTP environment, requests for comprehensive, integrated information for analysis isare very high.
. Normalization: Due to the reduction in data redundancy, normalization is very high for operative use. Data staging and lower performance are the reasons why there is less normalization in the Data Warehouse.
. Read access: An OLAP environment is optimized for read access. Operative applications (and users ) also need to carry out additional functions regularly, including change, insert, and delete.
