The management of data and information definitions as they relate to the overall data quality process is the most essential aspect of any customer relationship management, data warehouse, or other marketing database system. New business processes, data asset analysis, business requirements, supply chain management, customer interactions, and user requirements should all be considered when defining the foundation for an effective data quality based architecture.
At Satio Solutions, we believe the time invested in the Data Definition process early in the lifecycle of data quality based initiatives will inevitably save valuable time and create further cost reductions in the implementation phase of data warehouse and other marketing database systems. This disciplined approach to evaluating the various sources of information that will ultimately feed these and other types of business applications will ensure that:
- Data anomalies are discovered early in the and are factored into the design as opposed to being dealt with in a time-consuming, trial and error approach in the implementation phase of a given project
- A data model incorporates all possible data assets that have value to the organization
- Gaps between data that is desired and data that is available can be addressed
- Tables and other Data Transformation rules can be established to assure data quality
- Process Definitions for data element and database update can be established
- Address Standardization, Correction, and Validation procedures can be established
- Desired summary data can be defined to minimize processing requirements
- Derived data definitions can be established along with supporting algorithms and business functions
- Standard reporting mechanisms can be established
- System Administration processes for quality control can be established
- Procedures and processes to support Ad hoc Query can be established
Effective data definitions will provide the infrastructure for an organization to establish a clear competitive advantage for itself by implementing a comprehensive data management approach to improve productivity and enhance service or product offerings of the organization. The primary benefits will include streamlined processes, productivity improvement, increases in revenue, cost reductions, and opportunity for expanded customer lifetime value.
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