What is a warehouse and what should a modern data warehouse include?

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shukla7789
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What is a warehouse and what should a modern data warehouse include?

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Discover the clues about the different components of a modern data warehouse that will help you understand what a warehouse is.

Sep 14, 2022
In a world where data circulates in large quantities, having a data repository or warehouse becomes a fundamental requirement to achieve greater organizational capacity and make decisions in a correct and fast way. Thanks to technological advances, tools have been developed for the management and analysis of information in the business environment.






Over the past decade, the amount of data created, captured, copied vnpay database consumed worldwide has increased from 1.2 trillion gigabytes to 59 trillion gigabytes, representing growth of nearly 5,000% .

Source: Forbes



Warehouse: a definition
A data warehouse definition, or more specifically a data warehouse, could be the following: a data warehouse is a system used to report and analyze data that functions as a central repository of data integrating one or more disparate sources of information. They store current and historical data and are used to perform processing and create analytical reports for decision making in organizations.

A data warehouse has three general layers that, although not mandatory, are frequently used, depending on the architecture:

Integration layer where extracted raw data is stored and prepared.
Main layer of the data warehouse where data is adapted to the company's homogeneous data model.
Data marts and strategic marts layer , which provides specific extracts from the corporate data warehouse .
These layers often present complex internal business and transformation logic and are sometimes not easily distinguishable as separate architectural blocks. Recent developments have achieved considerable optimizations in each of these aspects.







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The basic components of a warehouse
Today , data warehouses are no longer just fed by information generated by internal systems. New formats, alternative data sources and different types of information add complexity to an essential structure in the knowledge generation process.
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