Data Warehousing

Data WarehousingProblemshigh demand for resourceshigh maintenance - the size an dvolume of data requires a high level of maintentacecomplexity of data integration - the integration of data coming from multiple source systems is highly complexCharacteristicsSubject=oriented data - warehourse if organized around the major subjects of ht e enterpriseIntegrated data - integrates data from diferent souce systemsm, must be made consistent to tpresent a unified view of data to the user data - data is not updated in real-time, it is refreshed from operational system regularlyTime-variant data - data is only accurate and valid at some point in tiem or over some time intervalDW info FlowsMetaflow - the processes associated with the management of the metadataInflow - extraction, cleansing and loading of data from source systems into DWOut flow - making data avaliable to end usersUpflw - adding value to the data through summarizing, packaging and distrition of the dataDownflow - archiving and backing up/recovering of dataBenefitsPotential high return on investment (ROI)Competitve advantage - by allowing access to data that can reveal previously unavailable, unknown inromation or patterns of the businessIncreased productivity of corporate decision makers - by creating an integrated database of consistent, subject-oriented, histroical dataComponentsMetadata - used to map data sources to a common view of information within the warehouseQuery Manager - management of user queries, directing them to the appropriate tables and scheduling the executiion of queriesLoad Manager/ETL Manager - extraction , transformation and loading of data into the warehouseWarehouse ManagerAnalysis of data to ensure consistencyTransformation and merging of source data from temp storageCreation of indexes and viewsBacking up & archiving dataETLinvovles tasks of capturing data from source systems, cleansing and transforming it, and loading the results into a target system