December 14, 2010 
Metadata management is a very important one in the entire data warehouse architecture (data warehouse architecture, please refer to the article - the basic structure of the data warehouse), but the hair a lot of the book which do not have a detailed metadata definition, or introduced in the end the data warehouse metadata what should be included. Here is my personal finishing some of the views of the metadata management, mainly from the two books Inmon data warehouse ", the Oracle documentation and personal that some meta data should be recorded in the data warehouse applications. Metadata definition metadata (Meta Data), as if from the literal point of view can not see ... »Read more: data warehouse metadata management November 16, 2010 
Is an article on the Business Intelligence (BI), in front of the articles describes data warehouses, multidimensional models and OLAP knowledge. This article summarizes the OLAP have some basic features, as well as its advantages embodied in the data processing, display and analysis. In fact, most of our time is imitation, reference in this or the example of others, when we go to these things when they have their own experience, we need to record these experiences, when we are able to summarize the whole implementation process when, in fact, that we have mastered the knowledge or skills. And it is ... »Read more: OLAP basic characteristics October 27, 2010 
The previous two articles in the blog: multi-dimensional model of the data warehouse and data cube and OLAP multidimensional models and OLAP some basic concepts described in this article is based on the depth extension of the two articles, introduces multidimensional OLAP in two important constituent elements - dimensional cubic structure and composition. May favor the Model, you can skip right in that regard is not very interested in students. ;-) Dimension (Dimension) dimension is used to describe the characteristics of things from different angles, the general-dimensional multi (Level), each Level will include some of the common or special ... »Read more: dimension (Dimension) and Cube (the Cube) August 29, 2010 
A previous article - the multidimensional data model of the data warehouse has a brief definition and structure of the multidimensional model, as well as the fact table (Fact Table) and the concept of the dimension table (Dimension Table). Multidimensional data model as a new logical model given the data organization and storage of forms, and truly reflects its advantages also need to model-based efficient operation and handling on the analysis, that is, OLAP (On-line Analytical Processing online analytical processing). Data cube on the data cube (Data Cube) It must be noted that the data cube Multidimensional Model ... »Read more: Data cube and OLAP August 17, 2010 
Many people may not understand the data warehouse is built based on the multidimensional data model for OLAP data platform on the article - the basic data warehouse architecture, we have seen that the data warehouse applications may be far more than that. But have to admit that the multidimensional data model is a major feature of the data warehouse, an important aspect of the data warehouse application and implementation, data organization and storage optimization, making it more suitable for analytical data query and access . The multidimensional data model definition and the role of multi-dimensional data model in order to meet the multi-level multi-angle data query and ... »Read more: the multidimensional data model of the data warehouse August 1, 2010 
The purpose of the data warehouse is to build integrated data analysis-oriented environment for enterprises to provide decision support (Decision Support). In fact, the data warehouse itself is not "production" of any data, at the same time itself does not need to "consume" any data, data from an external source, and open to external applications, which is why called the "warehouse", but not called "factory" reasons. Therefore, the basic structure of the data warehouse contains data inflow and outflow can be divided into three layers - the source data, data warehouse, data applications: It can be seen from the figure, the data warehouse comes from a different source data, and Provide a variety of number ... »Read more: data warehouse architecture July 20, 2010 
Integrated enterprises can get almost all of the data in the data warehouse for data analysis and decision support, including of course all the data that I mentioned in the web analytics data sources. These data into the data warehouse is nothing less than three types: structured data, semi-structured data and unstructured data, after conversion unified in some form, stored in a data warehouse, which is usually said ETL (Extract, Transform, Load, extract, transform, load) of the process. The following will mainly talk about the difference between these three types of data, respectively, including which source data as well as ... »Read more: Data warehouse source data type February 25, 2010 
I believe we all understand the four basic characteristics of the data warehouse: a subject-oriented, integrated, and relatively stable, record history, and the value of the data warehouse is based on four features embody: an efficient organization of data subject-oriented nature of the data warehouse has a highly efficient form of data organization, business database has more complete data system, clear data classification and stratification mechanism. Because all data have been cleaned and filtered before entering the data warehouse, so that the original data is no longer chaotic, to optimize the query-based forms of organization, improve data access, statistics and analysis of the efficiency of ... »Read more: The value of the data warehouse 
