ZT: A brief explanation of common nouns in data Warehouse

Data
ZT: A brief explanation of common nouns in 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 presents OLAP's 12 guidelines to describe OLAP systems:

Benchmark 1 OLAP models must provide a multidimensional conceptual view
Guideline 2 Transparency Guidelines
Benchmark 3 access capability speculation
Guideline 4 Stable reporting capability
Benchmark 5 client/server architecture
Criterion 6-D equivalence criterion
Guideline 7 dynamic Sparse matrix processing criterion
Guideline 8 Multi-user Support competency Guidelines
Guideline 9 non-restricted cross-dimension operations
Guideline 10 Intuitive data manipulation
Guideline 11 Flexible report generation
Guideline 12 non-restricted dimension and aggregation hierarchy ROLAP

Based on the 12 guidelines of Codd, each software development manufacturer has a different opinion, one of which is that the relational database can be used to store multidimensional data, so the star structure based on sparse matrix representation (star Schema) 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. is called Muiltdimension OLAP, referred to as MOLAP, on behalf of products have 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 adjust market strategies, reduce risk, and make the right decisions

CRM Customer Relationship Management (relationship Management), the Data Warehouse is based on the database technology, but with the traditional database application has a fundamental difference between the new technology, CRM is based on data Warehouse technology, a novel application. However, in terms of business operation, CRM should be regarded as an old "application". For example, the hotel's management of guest information, if a guest is a regular customer of a hotel, then the hotel will naturally know that the guest's certain habits and preferences, such as whether to like the roadside, whether smoking, like the big bed, like what kind of breakfast, 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.