A brief explanation of common nouns in data Warehouse

A brief explanation of common nouns in data data Warehouse
Data Warehouse in the middle of the 80 's, Mr. William H.inmon, the "Father of the warehouse", defined the concept of data warehousing in his book "Building Data Warehouses," and then gave a more precise definition: Data warehousing is a topic-oriented, integrated, A data collection that is related to time and cannot be modified. Unlike other database applications, a data warehouse is more like a process for the integration, processing, and analysis of business data that is distributed throughout the enterprise. Rather than a product that can be purchased. Data mart, or "small Data warehouse." If the Data warehouse is built on the enterprise-level data model. The Data mart is a subset of the enterprise-class data Warehouse, which is primarily for departmental business and is only geared towards a specific topic. Data marts can mitigate bottlenecks to access the data warehouse to some extent. The concept of OLAP online analytical processing (OLAP) was first proposed by the father of the relational database, E.f.codd, in 1993. At that time, Codd that the online transaction processing (OLTP) can not meet the end-user needs of database query analysis, SQL for the large database simple query can not meet the needs of user analysis. The user's decision analysis needs a lot of calculation to the relational database to get the result, and the result of the query can't meet the demands of the decision-makers. So Codd puts forward the concept of multidimensional database and multidimensional analysis, that is, OLAP. Codd to describe OLAP systems with 12 criteria: Guideline 1 OLAP models must provide multidimensional conceptual view guidelines 2 Transparency Guidelines 3 access capability inference Guideline 4 stable reporting Capability Guidelines 5 client/server architecture Guidelines 6-dimensional equivalence guideline 7 Dynamic sparse matrix processing criteria Guidelines 8 multiuser Support Capability Guideline 9 non-constrained cross-dimensional operating guideline 10 intuitive data manipulation guidelines 11 flexible report generation guidelines 12 unrestricted dimension and aggregation hierarchy ROLAP based on Codd 12 guidelines, each software development manufacturer opinions, one of the schools, It is believed that a relational database can be used to store multidimensional data, so the star structure (a star schema) based on sparse matrix representation appears. Later, the snowflake structure was evolved. In order to distinguish from multidimensional database, OLAP based on relational database is called relational OLAP, referred to as ROLAP. Represents a product with Informix Metacube, Microsoft sql Server OLAP Services. Molaparbor software strictly follow the definition of Codd, the establishment of a multidimensional database, to store online analysis system data, creating a multidimensional data storage precedent, and later many companies have adopted multidimensional data storage. It's called muilt.Dimension OLAP, referred to as MOLAP, on behalf of the product has Hyperion (formerly Arbor Software) Essbase, Showcase strategy and so on. Client OLAP is relative to server OLAP. Some of the analysis tool manufacturers recommend that some of the data download to local, to provide users with local multidimensional analysis. Represents a product that has brio designer,business Object. DSS Decision Support Systems (Decision Support System) are equivalent to data warehouse based applications. Decision support is the collection of all relevant data and information, processed and collated, to provide information for the decision management of enterprises, to provide the basis for decision makers. ETL Data Extraction (EXTRACT), conversion (Transform), cleaning (cleansing), loading (load) process. It is an important part of the data Warehouse, the user extracts the required data from the data source, cleans the data, and finally loads the data into the data warehouse according to the predefined data warehouse model. Ad hoc query, the most common database application of a query, the use of data warehousing technology, can allow users to face the database at any time, access to the desired data. EIS Leadership Information System (Executive information System) refers to an application designed specifically to access a data warehouse with a simple graphical interface in order to satisfy the information query needs of leaders who cannot focus on computer technology. BPR Business Process reengineering (Business process reengineering) is one of the important functions of data Warehouse, which uses data warehouse technology to discover and correct the malpractice in enterprise business process. Bi Business Intelligence (Business Intelligence) refers to the generic term for Data warehouse related technologies and applications. Refers to the use of various intelligent technology to enhance the business competitiveness of enterprises. Mining data Mining, the information mining is a decision support process, it mainly based on AI, machine learning, statistics and other technologies, highly automated analysis of the original data of the enterprise, to make inductive reasoning, from the mining of potential models, to predict customer behavior, Help decision-makers to adjust market strategy, reduce risk, make the right decision CRM Customer Relationship Management (relationship Management), Data Warehouse is based on database technology but also with traditional database application has a fundamental difference between the new technology, CRM is a new application based on data Warehouse technology. However, in terms of business operation, CRM should be regarded as an old "application". For example, hotel management of guest information, if a guest is a regular customer of a hotel, the hotel will naturally know some of the guests ' habits and preferences, such as whether they prefer to go by the roadside, whether to smoke, whether they like a big bed, what kind of breakfast they like, and so on. When guests come again, the hotel will provide the guest's favorite rooms and services without the guests ' own suggestions. This is a kind of CRM. Meta data metadata, information about data Warehouse, which is the key data related to data source definition, target definition, conversion rule and so on in the process of data warehouse construction. The metadata also contains business information about the meaning of the data, all of which should be kept properly and managed well. Facilitate the development and use of the Data Warehouse.