high demand for resources

high maintenance - the size an dvolume of data requires a high level of maintentace

complexity of data integration - the integration of data coming from multiple source systems is highly complex

Subject=oriented data - warehourse if organized around the major subjects of ht e enterprise

Integrated data - integrates data from diferent souce systemsm, must be made consistent to tpresent a unified view of data to the user

Non-volatile data - data is not updated in real-time, it is refreshed from operational system regularly

Time-variant data - data is only accurate and valid at some point in tiem or over some time interval

Metaflow - the processes associated with the management of the metadata

Inflow - extraction, cleansing and loading of data from source systems into DW

Out flow - making data avaliable to end users

Upflw - adding value to the data through summarizing, packaging and distrition of the data

Downflow - archiving and backing up/recovering of data

Potential high return on investment (ROI)

Competitve advantage - by allowing access to data that can reveal previously unavailable, unknown inromation or patterns of the business

Increased productivity of corporate decision makers - by creating an integrated database of consistent, subject-oriented, histroical data

Metadata - used to map data sources to a common view of information within the warehouse

Query Manager - management of user queries, directing them to the appropriate tables and scheduling the executiion of queries

Load Manager/ETL Manager - extraction , transformation and loading of data into the warehouse

Analysis of data to ensure consistency

Transformation and merging of source data from temp storage

Creation of indexes and views

Backing up & archiving data

invovles tasks of capturing data from source systems, cleansing and transforming it, and loading the results into a target system