cases, the star pattern is layered into the snowflake model, that is, the star pattern is further layered and the data redundancy is reduced.
To say so much, simply to answer two questions: Repeatability interactivity.
The two issues correspond to two entities, data warehousing data marts. Let's compare the differences between the two entities.
Search for "Inmon and Kimball" on Google, and you'll easily find the concepts of these two names, which are two of the best-known ways of data Warehouse architecture. In this ocean of information, however, you will find that almost all of the content can come to a conclusion, that is, to choose between Bill Inmon and R
political support is very important. It Gets the Data Warehouse project manager off the hook and puts the burden of the decision making process on senior Manag Ement ' s shoulders, where it belongs. 三、二级 Data Mart (Second-level-Marts) After you has represented all the major production sources in the enterprise with First-level
Auto House Data Platform architectureInternet Enterprise Data Warehouse construction is to use the bottom-up approach, or top-down approach. If you are an architect in the data division, how do you plan a data warehouse? At the 20
The purpose of the data Warehouse is to build an integrated data environment for analysis, providing decision support for the Enterprise (decision supports).
The basic architecture of data warehouse mainly consists of the process
Technical Architecture Design of the data warehouse system
Author: Cheng Xiaoxu
Because the technical solutions described in this article are derived from online production systems, they will not provide complete and detailed technical solutions, nor provide source code. You are welcome to discuss technical solutions and exchange design experiences.
According to the author's experience in the Data Warehouse ETL internship in Teradata and Main Street network, we can understand the relationship and difference between them in architecture design.
Teradata is generally the enterprise-class data Warehouse, in the Teradata
The following content, is the author in the study and work of some summary, of which the concept of most of the content from the book, the practical content mostly from their own work and personal understanding. Due to the lack of qualifications, there will inevitably be many mistakes, I hope to criticize. Overview
The Data warehouse contains a lot of content, which can include
, and object relationships from the logical model of the Business System Data Model.
From the author's point of view, the biggest advantage of inmon's paradigm modeling method is that from the perspective of relational databases, combined with the data model of the business system, data warehouse modeling can be easil
limited to relational databases, the flexibility and performance of the entire data warehouse model are limited in some cases, especially when the underlying data of the Data Warehouse is summarized to the data in the
Bill Inmon and Ralph Kimball, who were exposed to two names at school, were unfamiliar to most of the two Americans, but they were a resounding figure in the database field. Bill Inmon, known as the "Father of the Data Warehouse", he can now see a lot of scholarly papers and articles on the Web, and Wikipedia's introduction to him should be very comprehensive: in
focus on transaction processing, it not only improves the efficiency of transaction processing, but also optimizes the analysis and processing capabilities.In traditional enterprise transaction processing systems, each department retains part of the data according to its own transaction processing needs, and the relationship between each module is not close. Although some of the customer's information can also be obtained from these systems, but far
The business environment is changing rapidly, and so is the type of business data. A successful Data warehouse solution is based on flexible design that adapts to changing business data. The architecture of data
associated with the warehouse, including the ELT jobs that were created earlier in design Studio.
About this tutorial
This tutorial is the 1th part of the introductory series of Informix Warehouse Feature. This tutorial describes the Informix Warehouse option and its components and architecture. Outlines the key con
intelligence can assist business decision-making, which can be either operational or tactical or strategic. To turn data into knowledge, you need to leverage technologies such as data warehousing, online analytical processing (OLAP) tools, and data mining. Therefore, from the technical level, business intelligence is not a new technology, it is only
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
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