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This article is about what the concept of data warehouse is. The editor thinks it is very practical, so share it with you as a reference and follow the editor to have a look.

Overview

W.H.Inmon, the founder of the concept of data warehouse, defines the data warehouse in his book "Building a data Warehouse": a data warehouse is a collection of data that is subject-oriented, integrated, relatively stable and constantly changing with time (at different times). It is used to support the decision-making process in operation and management, and the data in the data warehouse is subject-oriented, corresponding to the application-oriented of traditional databases.

Topic oriented (Subject-Oriented)

Topic is a standard for classifying data at a higher level, and each topic corresponds to a macro area of analysis. Different from the general OLTP system, the data model design of data warehouse focuses on classifying the data into the same topic area (subject area) according to its meaning, so it is called topic-oriented. For example, Party, Arrangement, Event, Finance, Market, Sales, Product and so on.

Integration (Integrated)

The data in the data warehouse is extracted from the original decentralized database, because the source data corresponding to each topic of the data warehouse may be duplicated or inconsistent in the original distributed database, and the comprehensive data can not be obtained directly from the original database, so the data must be processed and integrated before entering the data warehouse. This is a key step in the establishment of a data warehouse, first of all to unify the contradictions in the original data, but also to change the original data structure from application-oriented to topic-oriented.

Historic (Nonvolatile)

The stability of the data warehouse means that the data warehouse reflects the historical data, not the data generated by daily transactions, and the data is rarely or not modified after being processed and integrated into the data warehouse.

Time-varying (Time-Variant)

The non-updatability of the data in the data warehouse is for the application, that is, the data update operation is not carried out when the user carries out analysis and processing. However, it does not mean that the data in all data warehouses will never change, but will change over time during the whole data generation cycle from data integration to final deletion. Data warehouse is a collection of data at different times, which requires that the time limit for data preservation in the data warehouse can meet the needs of decision analysis.

The value of data Warehouse

Efficient data organization

The subject-oriented characteristics determine that the data warehouse has an efficient data organization form, a more complete data system, a clear data classification and hierarchical mechanism that the business database can not have. Because all data are cleaned and filtered before entering the data warehouse, so that the original data is no longer disorganized, based on optimizing the organizational form of query, effectively improve the efficiency of data acquisition, statistics and analysis.

Time value

The construction of the data warehouse will greatly shorten the time to obtain information. As a collection of data, all information can be obtained directly from the data warehouse. The biggest advantage of the data warehouse is that once the underlying ETL process from various data sources to the data warehouse is built, then information from all aspects will flow into the data warehouse every day in the form of automatic task scheduling. As a result, the efficiency of all data acquisition based on these underlying information can be improved rapidly.

From the application point of view, the use of data warehouse can greatly improve the efficiency of data query, especially for massive data associated query and complex query, so data warehouse is conducive to achieve complex statistical requirements and improve the efficiency of data statistics.

Integrated value

Data warehouse is a collection of all data, including log information, database data, text data, external data, etc. are integrated in the data warehouse. For applications, it realizes the association of all kinds of different data and makes multidimensional analysis more convenient. It provides the possibility for data analysis and decision-making from multi-angle and multi-level.

Historical data

Recording history is one of the characteristics of data warehouse. Data warehouse can restore product status, user status and user behavior at historical points in time, so that it can better trace back history, analyze history, track users' historical behavior, better compare and summarize history, and predict the future according to history.

Thank you for reading! This is the end of the article on "what is the concept of data Warehouse". I hope the above content can be of some help to you, so that you can learn more knowledge. If you think the article is good, you can share it for more people to see!

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