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High level Data modelling is the process of define and analyze the data requirement.
Data Sources
data modelling is used for organising and structuring of data. we can get overview through generic modelling. organising of data means representing the data in such a way that it comes in a particular order via graphical representation.
provides aggregate, high-level data
Granularity refers to the level of detail of the data stored fact tables in a data warehouse. High granularity refers to data that is at or near the transaction level. Data that is at the transaction level is usually referred to as atomic level data. Low granularity refers to data that is summarized or aggregated, usually from the atomic level data. Summarized data can be lightly summarized as in daily or weekly summaries or highly summarized data such as yearly averages and totals.
Select the request estatus Queue high-level
Select the request estatus Queue high-level
A high level data model serves the database designer by providing a conceptual framework in which to specify, in a systematic fashion, what the data requirements of the database users are, and how the database will be structured to fulfill these requirements.
High level data link control
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Select the request estatus Queue high-level
High level Data link Control
A conceptual data model is a high-level overview of the structure and relationships within a database. It focuses on the entities, attributes, and relationships between entities without going into the specifics of how the data will be implemented in a physical database. It serves as a blueprint for designing a database system.