What is the data layer for etl processing of data?

The data layer that performs etl processing on data is: data loading layer. ETL is the process of loading business system data into the data warehouse after extraction, cleaning and conversion. The purpose is to integrate scattered, messy, and non-standard data in the enterprise to provide analytical basis for enterprise decision-making.

The operating environment of this tutorial: Windows 10 system, Dell G3 computer.

The data layer that performs etl processing on data is: data loading layer.

ETL (Extract-Transform-Load, data warehouse technology) is the process of extracting (extract), cleaning and transforming (transforming) the data of the business system and then loading (loading) it into the data warehouse. The purpose is to integrate scattered, messy, and non-standard data in the enterprise to provide analytical basis for the enterprise's decision-making. ETL is an important link in the BI (Business Intelligence) project.

Description of each layer of the data warehouse:

1. Data loading layer: ETL (Extract-Transform-Load)

2. Data operation layer: ODS (Operational Data Store)

3. Data warehouse layer: DW (Data Warehouse)

• Data detail layer: DWD (Data Warehouse Detail)

• Data middle layer: DWM (Data WareHouse Middle)

• Data service layer: DWS (Data WareHouse Service)

4. Data application layer: APP (Application)

5. Dimension surface layer: DIM (Dimension)

Benefits of layering:

• Clear data structure: Each data layer has its scope and responsibilities, making it easier to locate and understand when using tables

• Reduce Repeated development: standardize data stratification and develop some common middle-tier data, which can greatly reduce repeated calculations

• Unified data caliber: provide unified data export through data stratification, Unify the data caliber for external output

• Simplification of complex problems: Divide complex tasks into multiple steps to complete. Each layer only processes a single step, which is relatively simple and easy to understand. When there is a problem with the data, you don't need to repair all the data, you just need to start repairing it from the problematic step.

• Shield the exception of the original data: there is no need to change the business once and re-access the data.

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