Introduction
With the rapid development of China's financial industry, it is an urgent problem for the bank to support the decision analysis by classifying and storing the customer data, analyzing the automatic discriminant of the various factors, and digging out the information needed by the bank managers and the business analyst in the presence of a large amount of data.
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
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
How data builds a bank data warehouse
Song Yuchang, No. 11th Xinhua East Road, Dengzhou, Henan, China.
As a new technology in data management field, the essence of Data Warehouse technology is to put forward a comprehensive solut
A data warehouse is an environment rather than a product that provides current and historical data for decision-making support. This data is difficult or cannot be obtained in traditional operational databases. Data Warehouse Tech
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
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
Original address
I. Definition of metadata
According to the traditional definition, metadata (Metadata) is data about data. In the Data warehouse system, metadata can help data warehouse administrators and developers of
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
server|sql| data
Partitioned views join horizontal partitioned data from a group of members so that the data looks like it comes from the same table. SQL Server 2000 distinguishes between local partitioned views and distributed partitioned views. In the local partitioned view, all related tables and views reside on the same instance of SQL Server. In a distribute
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
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
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
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
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
This article discusses two common methods in data warehouse model design. In the application environment of data warehouses, there are two types of load: one is to answer repetitive questions, and the other is to answer interactive questions. Dynamic query has obvious interactive features. This interaction process is often called
Instance construction process and analysis
1Now we will analyze and discuss it with a simple example.Ms SQL ServerData warehouse construction process. In fact, the construction of the Data Warehouse is quite complex. It combines the front-end technology of the data warehouse
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