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
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.
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
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
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
handles plus stdin, stdout, stderr, and so on is 20.
Although a mixed-record structure is appropriate for non-relational or NoSQL APIs, because there is no pattern required, developers often face situations where a technique is needed to use a pattern. A consistent pattern definition for some software using SQL (or ODBC, etc.) is required, such as a large number of third-party reporting and analysis tools, including Crystal Reports and Excel, as wel
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
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 was reproduced from: http://coolshell.cn/articles/7270.html ================================================ Full-text translation from the wall of the article "NoSQL Data Modeling techniques", translation is not good, please forgive me. After reading this article, you may feel a little bit about NOSQL data
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
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
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
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