federated data warehouse

constructs dimension Data Warehouse in the form of star model or snowflake model, in which data mart is closely combined with dimension Data Warehouse, and data mart is a logical subject domain in

], i.tracestate, ls. Syncdate, I.lastfollowdate, I.lastfollowdesc, I.lastfollowusername, I.saleschannelname, Sh.M Onthlyaccount, I.receiver, I.country, I.province, i.city, I.orderno, I.invoicecode, I.tracestatedate, I.tracestateuser, I.salesgroupid, I.salesuserid, I.salesusername, i.or Derid, I.customername, I.customerphone, I.printcheckdate fromWot_Inventory.dbo.Invoice i Left JOINWot_Inventory.dbo.Logistics ls onLs. Invoiceid=I.invoiceid Left JOINWot_Sales.dbo.Shipper SH onI.shipperid=Sh

In fact, in MySQL, multi-table joint update is not difficult.Grammar:UPDATE SET col_name1=[, COL_NAME2=EXPR2 ... ][WHERE where_definition]Example:UPDATE SET table1.value=Table2.value, a.type=WHERE table1.sid=Similarly, in SQL Server, it is possible to use federation as a simple implementation:UPDATE SET col1=fromINNERJOIN on t1.col2=However, unfortunately, in SQLite does not support such a syntax, it is not in SQLite does not support multi-table joint update it? Of course not, in fact, SQLite in

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

Design | Data building Data Warehouse What do you want to do? Generally, there are two main areas of data Warehouse construction: 1. Interface design with operational database. 2. The design of the data

Data warehouse and data mining are two big concepts. They are very mature in foreign countries. In China, with the accumulation of enterprise data and the maturity of ERP in the past few years, data warehouse and

　　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

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

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

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

Overview This article discusses the role of data partitioning in data warehouses. Relational data warehouses and Analysis Services cubes support data partitioning. The logical concept of partitioning is the same in the two engines of Microsoft®sql Server™: Horizontal partitioning of

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