One example of this characteristic is that a terabyte of data may have 50GB that are actively used and 950GB that are accessed perhaps only once a month or once a quarter. The organization pays the same for the data regardless of how frequently it is used. The data warehouse administrator can either archive the inactive data or place it in near-line storage. Accessing the inactive data, moving it to near-line storage, then deleting the data from the data warehouse defines the separation.
While it is true that all data warehouses face separation, the degree of separation varies among warehouses, based on these factors:
- Size of the warehouse
- Type of business the warehouse supports
- Who uses the warehouse
- What kind of processing is being done
- Level of sophistication of end-user analysts
Critical Success Factors
There are three critical success factors that each company needs to identify before moving forward with the issue of data quality:
- Commitment by senior management to the quality of corporate data
- Definition of data quality
- Quality assurance of data.
The senior management commitment to maintaining the quality of corporate data can be achieved by instituting a data administration department that oversees the management of corporate data. The role of this department will be to establish data management standards, policies, procedures, and guidelines pertaining to data and data quality.
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