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Why layer data warehouses? Use space for time and a large amount of preprocessing to improve the user experience (efficiency) of the application system. Therefore, a large amount of redundant data exists in the data warehouse; If there is no hierarchy, changing the business rules of the Source Business syste
The original: "Bi thing-the art of data" understanding Dimension Data Warehouse-fact table, dimension table, aggregation tableFact tableIn a multidimensional data warehouse, a table that holds a detailed value or fact for a measure is called a fact table. A fact table that s
The construction process and method of data warehouse system is different from the process and method of building the traditional operation type processing system, the construction of Data Warehouse system has two difficulties: first, how to guarantee the data quality, make
Fact tableIn a multidimensional data warehouse, a table that holds a detailed value or fact for a measure is called a fact table. A fact table that stores sales and sales by state, product, and month has 5 columns that are conceptually similar to the following example. Sate Product Mouth Units Dollars WA Mountain-100 January 3 7.95
To illustrate their relationship, we have to talk about business intelligence. From a technical point of view, the process of business intelligence is based on the data warehouse in the enterprise by the online analysis and processing tools, data mining tools, and the professional knowledge of decision planners, obtain useful information and knowledge from
Perhaps many people understand that the data warehouse is built on the basis of multidimensional data model for OLAP data platform, through the previous article-the basic architecture of the data Warehouse, we have seen that the
About star schema In the construction of the Data Warehouse, the star pattern shown in the following illustration is almost the most commonly used. It is called star mode because the E-R graphic in the pattern is like a star (it feels strange to say). NBSP as shown in the figure, the center is a large fact table with some dimension tables around it. The fact table contains the primary information fo
Policy | data 6 Strategies of Data Warehouse implementation In the implementation of the data warehouse, the need for theoretical guidance, with the development of data Warehouse t
Objective:Ready to systematize a set of distributed Data Warehouse Modeling Practice Guide, the first list of the table, is to design a goal for themselves.The first part of the basic articleChapter One concept and definition of data Warehouse1.1 Data Management System1.2 Data
Data currently, the term Data Warehouse does not yet have a unified definition, the famous data Warehouse expert W.h.inmon in his book, "Building The Data Warehouse", gave the following
warehouses, as follows:In general, I agree with the new generation of data warehousing, which is easy to use, efficient, extensible, data sharing, etc., but it is difficult for me to disagree with the comparison, especially in the speed, expansion two. Traditional Data Warehouse, the size of the
Data Warehouse is a comprehensive technology and solution based on data management and application. The successful implementation of data warehouses has a significant impact on the cultivation of a culture of knowledge sharing. Currently, the data
The common dwh architecture is as simple as figures 2 and 3. Generally, for an enterprise, the data lifecycle is 5-7 years, especially for detailed data. The lower the data granularity level, the shorter the lifecycle, the higher the data granularity and the longer the lifecycle. For the flow account
Compare | data Comparison of the characteristics of nine large data warehouse schemes China Institute of Electronic Equipment Systems Engineering Wang Jiannu Lidompo Powerful companies such as IBM, Oracle, Sybase, CA, NCR, Informix, Microsoft, and SAS have launched their own data warehousing solutions (through acqui
Cloud computing and data warehousing are a reasonable couple. Cloud storage can be scaled on demand, and the cloud can contribute a large number of servers to a specific task. The common function of Data Warehouse is the local data analysis tool, which is limited by calculation and storage resources, and is limited by
Just a few days ago, a user participated in a job interview for an enterprise. He applied for the DBA of the company and was responsible for data analysis. This company successfully completed the process. Until the person in charge of the company. The owner only gave him an interview question: Let's talk about the differences between the database and the data warehouse
Basic concepts: 1. Multi-dimensional dataset: a multi-dimensional dataset is the main object in Online Analytical Processing (OLAP) and a technology that allows quick access to data in a data warehouse. A multi-dimensional dataset is a collection of data. It is usually constructed from a subset of a
According to the Informix Data Warehouse System implementation methodology, we can divide the data warehouse implementation into the following steps: 1. Business Demand Analysis Business Requirement analysis is the basis for data warehou
server|sqlserver| data The construction and analysis of SQL Server Data Warehouse (i) Basic concepts: 1. Cubes: Cubes are the primary object in online analytical processing (OLAP) and are a technology that allows fast access to data in a data
In general, two monitored operational components in a data warehouse environment are the use of data and data stored in the Data warehouse. Monitoring data in a
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