data warehouse design tutorial

Oracle Data Warehouse creation tutorial. How to create a data warehouse, create an example, think of graduation design requirements, recently began Oracle's Warehouse modeling practice,

the groundwork for deployment and execution Deploy a project, a location, and all the objects under the module, which do the following: DDL, DML, Control File, workflow code, job generation code, or ABAP, and so on, the generation of code on the target user's database, The deployment of the DDL statement completes the generation of the object on the target user's database, and DML, Control File, Workflow, and job require the next execution to actually complete Perform (execute) work to

First, what is a data warehouse The traditional data warehouse concept is that data warehouse is a structured data environment for decision Support System (DSS) and on-line analysis app

. This is the value of the data warehouse. So how can we get data into a data warehouse? One of the technologies used is ETL. The following is a detailed definition of ETL: As the core and soul of DW, ETL (Extract-Transform-Load) can be integrated according to unified rule

, subtract, or multiply these columns. Dimensions are more based on themes. In this example, you have athlete information dimensions, time and date dimensions, and so on. Columns in multiple dimensions are usually not computed or weighted. In this example, the key that connects a dimension table to a fact table is playerID. In simple terms, sometimes you need to use the tools that are in front of you. Anyone who has worked on IT for some time may tell you that the right tool for a job is not

) three parts. four, the anchor model The anchor model is made up of Lars. Rönnbäck is designed to design a highly scalable model, the core idea: All extensions are only added rather than modified, so it will model specifications to 6NF, basically into the K-V structure model. The anchor model consists of:anchors, Attributes, Ties, Knots , and the relevant details can be referred to anchormodeling-agile information modeling in evolving

. Data Warehouse Model Through the above figure, we can easily see that during the modeling process of the entire data warehouse, we need to go through four steps: Business Modeling and generation of business models are mainly used to resolve and program the business layer. Domain Modeling: Generate doma

The life cycle approach provides a roadmap for the development of data warehouses, and the overall structure and steps of the life cycle approach are Define Business requirements Technical path Technical Architecture Design Selection and installation of products Data path Dimension modeling Physical

Microsoft vs. Yahoo! The long-running purchase war may put many people tired of news. But today we see this about Yahoo! The technical news is worth reading: Size matters: yahoo claims 2-petabyte database is World's biggest, busiest. Yahoo! VP Waqar Hasan of disclosure Yahoo! The current data warehouse capacity is 2 Pb. It is used to analyze 0.5 billion of user access behavior every month and process 24 bil

Adopt flexible and effective methods to plan, design, and implement Basic Data Warehouse solutions based on IBM DB2 Data Warehouse Edition. Part 1 of this series will focus on the customer interaction process and plan data

ModelingTo generate a business model, which mainly solves the business-layer decomposition and programming. Domain ModelingGenerate a domain model, which is mainly used to abstract the business model and generate a domain conceptual model. Logical ModelingTo generate a logical model. It mainly refers to the logic of the conceptual entities of the domain model and the relationships between entities at the database level. Physical ModelingThe physical model is mainly used to solve physical and

by the design and management personnel of the data warehouse for development and daily management. Includes: Data Source Information; description of data conversion; definition of objects and data structures in the

metadata. Technical metadata is the data used by the design and management personnel of the data warehouse for development and daily management. Includes: data source information; description of data conversion; definition of obj

categories, technical metadata and business metadata, depending on the purpose. Technical metadata is the data that the data warehouse design and management personnel use to develop and manage the Data Warehouse daily. Includes:

by the design and management personnel of the data warehouse for development and daily management. Includes: Data Source Information; description of data conversion; definition of objects and data structures in the

data At present, the total number of dial-up users in Guangdong Public multimedia communication network has reached 700,000. According to business needs analysis, Guangdong province 163/169 net to 2002 end of the total number of users will reach more than 8 million, of which dial-up registered users up to 4 million, the main call users 3 million, card users 1 million, line users will also reach more than 10,000 households. There is a lot of important

basis of data warehouse, there are two kinds of analytical tools, one is OLAP for analytical work, the other is data mining of predictive work. The idea of data mining is to find a correlation rule like "beer and diapers". But the current technology system, whether in China or in other countries of the world, shouldar

, granularity, dimension, measurement value, multi-dimensional data model, and dw2.0. Chapter 3 describes how to design a data warehouse and introduces the concept of metadata. Chapter 4 is the most part of the course class. It took a lot of time to build a Bi system from start to end and finally provided a Web Service

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