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The following content is taken from the Internet and sorted out. Terms: Bi (Business Intelligence): Business Intelligence, DW (data warehouse): Data Warehouse. For details, see section Q1. OLTP (on-line transaction processing): Online Transaction Processing It is also known as a transaction-oriented processing syste
Data Warehouse and data mining--a sharp weapon to participate in the competition of digital telecommunication enterprises The solution of Guangdong Telecom Data Warehouse based on Sybase Guangdong Institute of Telecommunication Science and technology 1 overview With the o
Data Warehouse--digging in "beer and diapers" 01-5-21 04:19:25 Interlocutor: Host: Cheng Hung--"Computer World" reporter Home: Mengxiao--Renmin University of China School of Information Professor Qi-"Data Warehouse Road" website host it Manufacturers: Yang Shunsheng--NCR Greater China Market and partner g
Many companies use data warehouses for data analysis. Generally, they extract data from online backup databases (such as mirror, logshipping, and slave) to the ods layer. From the ods layer to dw to dm, especially from the ods lay
Data Three CIF Case-sap BW The main feature is that ERP vendors provide the entire architecture, which saves a lot of design work, and reduces the cost of design and development, encapsulation of the business in BW, reducing the difficulty of long-term maintenance. ERP data resources are very rich and valuable, should be an important source of data warehousing,
. This is what many vendors once talked about. The two methods can be used flexibly based on different needs. Most db software uses row-based storage, and column-based storage features efficient single-column value compression. When selecting fewer columns, the io requirement is very low and the speed is fast, however, the compression efficiency of Row-store databases is also rapidly improved. Most of the requirements are to select row data for observ
> ODS Layer Mainly responsible for collecting business systems and keeping relevant business data for a certain period of time. Of course, you can also meet the user's query requirements for detail data, but also can be counted as a detail warehouse. > Data
Data warehouses are subject-oriented, integrated, non-updatable, and changing over time, which determines that the system design of a data warehouse cannot be designed with the same design method as the traditional OLTP database.The original requirements of the Data Warehouse
Data Warehouses are subject-oriented, integrated, non-updatable, and constantly changing over time, these features make sure that the system design of the data warehouse cannot be the same as that of the traditional OLTP database. The original requirements of the data warehouse
a common subject or business field. The following describes how to create an information package chart through information packaging technology to determine the topic and metadata in the data warehouse.3.4.1 information packaging technology1. Basic use of information packaging technology The information packaging method is a top-down design method, which focuses on one or more topics of an enterprise from
What is a data warehouse? Bill inmon, father of data warehouse, was widely accepted in the definition proposed in building the Data Warehouse published in 1991, A data
First, the Data WarehouseThe standard definition of the Data Warehouse concept is relatively high in the industry, as proposed by Bill Inmon, the father of the Data Warehouse, in the book "Building The Data
First, the Data WarehouseThe standard definition of the Data Warehouse concept is relatively high in the industry, as proposed by Bill Inmon, the father of the Data Warehouse, in the book "Building The Data
in multiple legacy locations, and in some cases even relatively small data sources, such as Microsoft Excel spreadsheets, can be stored on file shares. Clean up data When you merge OLTP data into a data warehouse, you provide an opportunity to clean up your
Ho, August See a colleague on the desktop there is a Data Warehouse Toolbox Third edition, this blog simply discusses the Data Warehouse modeling general process and modeling methods (mainly practical experience and network data integration) First describe the application
Data WarehouseThe purpose of the Data Warehouse is to build an integrated data environment for analysis, providing decision support for the Enterprise (decision supports). In fact, the data warehouse itself does not "produce" any
Schema | Data Microsoft Data Warehouse architecture Absrtact: This article briefly introduces the data warehouse using the Microsoft Data Warehouse architecture, discusses the function
Design | data [For the convenience of their own reading so collect and organize here, Www.DMResearch.net] 21 Principles of Data Warehouse design --7 steps, 7 taboos and 7 ways of thinking Seven steps to efficiently implement a data warehouse The
21 principles of data warehouse design-7 steps, 7 taboos and 7 ideas Seven steps for efficient data warehouse implementation The data warehouse has some kinship with our common RDBMS systems, but it is different. If you have n
Seven steps for efficient data warehouse implementation The data warehouse has some kinship with our common RDBMS systems, but it is different. If you have not implemented a data warehouse, from setting goals to providing design
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