blendingplan

A blendingplan is a formal framework or document that prescribes how to combine data from multiple sources to create a unified dataset for analysis and reporting. It defines the scope, objectives, and governance for the blending activity.

Typically, a blendingplan includes the list of data sources, key fields for joining, and the data attributes to be included. It also specifies transformation rules used to align schemas and data types, so that the blended dataset is coherent and analyzable.

The plan documents the join strategy (such as inner or left joins), how duplicates and missing values are handled, and how conflicting data are treated. It also outlines data quality requirements and reconciliation procedures to verify the blended results.

Additional elements commonly covered are metadata and lineage, ownership and accountability, refresh cadence and scheduling, and access controls. Performance considerations, validation tests, and rollback procedures may also be described to support reliable operation.

Use and context: In analytics and business intelligence projects, a blendingplan helps data engineers and analysts construct reproducible data blends for dashboards and models, ensuring consistency of results across reports and over time.

Relation to other concepts: The blendingplan is related to data integration, data fusion, ETL/ELT processes, and data governance. While not standardized, it serves as a practical blueprint for coordinating interdisciplinary effort and maintaining transparency in data preparation.

See also: Data integration, Data governance, ETL, Data quality.