data warehouse modernization

Data Warehouse (Data warehousing)-"set off your Hijab" I'm here to say some of my beginner's understanding and views, I hope these can be as a simple introduction to those novice friends, but also want to play a good effect. When it comes to data warehousing, let's take a look at the background he's producing. Since Db

Number of materialized views synchronized 1. The purpose is to synchronize some data in the production database to the Data Warehouse. Considering the cost and convenience, the method of regularly refreshing the Materialized View Number of materialized views synchronized 1. The purpose is to synchronize some data in th

Label:In short, the database is a transaction-oriented design, the Data Warehouse is a theme-oriented design.Databases generally store online transaction data, and data warehouses typically store historical data.Database design is to avoid redundancy as far as possible, generally adopt the rule of conforming to the pat

Model design of Data WarehouseA. Data Modeling MethodologyThe design of the Data warehouse model follows the design principle of "top-down and gradual refinement".The design of the model is divided into three stages:1, conceptual modelThe scope and use of the business, from the height of the abstract summary, that is,

Application background China Unicom has a national scale of public telecommunications network, operating a variety of basic telecommunications business and value-added telecommunications services, the formation of mobile (GSM, CDMA), 193 long-distance, VoIP, 165 (Internet and E-commerce), paging, local calls, value-added services, such as a variety of business coexistence and common development pattern. How to give full play to Unicom's comprehensive advantages, to achieve flexible marketing st

BI architecture and data warehouse design (14:26:41)BI architecture and data warehouse design A data warehouse solution is often related to a large Bi strategy. When you plan to use the fast tracing architecture, the most impo

Data warehouse model development methodology (for future reference) Based on the business data model, the data model of the data warehouse system is formed through the eight-step conversion process: Procedure Action

General Purpose = Take account of both OLTP and OLAPTransaction processing =OLTPData Warehouse =olapCustom DATABASE = Custom Gold dividing line (deep analysis) ******************************* Data processing can be roughly divided into two main categories: online transaction processing OLTP (on-line transaction processing), online analytical processing OLAP (On-line Analytical Processing). OLTP is the ma

product Dimension has a product family, a large class, and a small class of three attributes, which defines [ classify layer level, take advantage of these three properties directly, That is, each level is a property of a member. The other is between the dimension members, such as hr , each level is a specific dimension member, that is, each level is one or more dimension members, Each level contains multiple properties. The latter level is often persisted in the database in a recursive man

Oraclew.alservicesapplication (OFSA) Technology Platform: Includes OracleWarehouseBuilder data warehouse building tool, Oracle8i Database, OracleExpress multi-dimensional database, CommonWarehouseMetadata Common Data Warehouse metadata management tool, OracleInternetDevelopSuites Business Intelligence Oracle Financial

One-network fund settlement analysis system for Guangdong expressway Based on the Data Warehouse Star Model Magenfeng(Guangdong Union Electronic Service Co., Ltd., Guangzhou 510300, China) SummaryThe star mode is a well-known concept in the Data Warehouse Based on relational databases. the design concept of the star co

First, preface　　Changes in the work content, resulting in a return to the Data Warehouse model architecture and design, so take a moment to compare the system Review Data Warehouse modeling and system building knowledge system, recorded, as a note it.Second, the model　　No matter how

This paper gives the basic concept of SQL Server Data Warehouse, and uses the example construction process to analyze, for everyone's reference! Basic concepts: 1. Cubes: Cubes are the primary object of online analytical processing (OLAP) and are a technology that allows fast access to data in a data

"Guide" This article describes how to build a simple data warehouse in SQL Server and analyze related issues. 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 warehouse