Data warehouse
In the mid-1980s, "Data Warehouse's Father" William H.INMON defines the concept of data warehouses in its "establishing data warehouse", and then gives a more precise definition: Data warehouse is in business The theme, integrated, and time-related, unmodified data collection in management and decision. Different from other database applications, data warehouses are more like a process, and the process of integrating, processing and analysis of business data distributed across the enterprise. Not a product that can be purchased.
Data Mart
Data market, or called "small data warehouse". If the data warehouse is built on the enterprise-level data model. Then the data market is a subset of the enterprise-class data warehouse, and he mainly facing the department-level business and is just a specific topic. Data markets can mitigate the bottleneck access to the data warehouse to a certain extent.
OLAP
The concept of online analysis processing (OLAP) was first proposed in 1993 by the parent E.f.codd of the relational database. At that time, CODD considered online transaction processing (OLTP) that the terminal user needs to query the database query analysis, and the simple query of SQL to large databases does not meet the needs of user analysis. User's decision analysis requires a lot of calculations for relational databases to get results, and the results of the query do not meet the needs of decision makers. Therefore, CODD proposes the concept of multi-dimensional database and multi-dimensional analysis, that is, OLAP. CODD proposes 12 guidelines for OLAP to describe the OLAP system:
Guidelines 1 OLAP model must provide multidimensional conceptual view
Guidelines 2 Transparency Guidelines
Guidelines 3 Access capacity speculation
Guidelines 4 Stable Report Ability
Guidelines 5 Customer / Server Architecture
Top 6-dimensional equivalence
Criterion 7 Dynamic Sparse Matrix Treatment Guidelines
Guidelines for more than 8 users support capability
Guidelines 9 Non-restricted cross-dimensional operation
Guidelines 10 intuitive data manipulation
Guideline 11 flexible report generation
Guide 12 Unrestricted dimension and aggregation level
ROLAP
Based on CODD 12 guidelines, various software development manufacturers see the benevolence, one of them, believes that the multidimensional data can be stored along the relational database, so that the star structure based on the sparse matrix representation method will appear. Later, I evolved the snow structure. In order to distinguish between the multi-dimensional database, the OLAP based on the relational database is referred to as RELATIONAL OLAP, referred to as ROLAP. Representing products include Informix Metacube, Microsoft SQL Server Olap Services.
MOLAP
Arbor Software strictly follows the CODD definition, and has established a multi-dimensional database from its own, and stores the online analysis system data, and creates the forefront of the multi-dimensional data store, and many companies have used multi-dimensional data stores. It is called Muiltdimension OLAP, referred to as Molap, represents the product has Hyperion (formerly Arbor Software) EssBase, Showcase Strategy, etc.
Client OLAP
Relative to Server OLAP. Some analysis tool manufacturers recommends downloading some data to the local, providing users with local multi-dimensional analysis. Representing the product has Brio Designer, Business Object.
DSS
Decision Support System (Decision Support System) is equivalent to a data warehouse. Decision support is to collect all relevant data and information. After processing, it provides information to provide information for the company's decision-making management, providing a basis for decision-making.
ETL
Data Extract, Transform, Cleansing, Loading (LOAD) process. An important part of building a data warehouse, the user draws the required data from the data source. After data cleaning, the data is finally loaded into the data warehouse in a pre-defined data warehouse model. Ad hoc query
A query, the most common query of the database application, using data warehouse technology, allows users to facilitate the database to get the desired data.
EIS
Executive Information System, refers to an application that visits the data warehouse in a simple graphical interface in order to meet the information query requirements that cannot focus on leaders of computer technology.
BPR
Business process reengineering, refers to the important role of the data warehouse in the use of data warehouse technology, discovered and correcting the drawing of the corporate business process.
BI
Business Intelligence, refers to the generality of the warehouse related technologies and applications. Refers to the use of a variety of intelligent technology to enhance the business competitiveness of the company.
Data Mining
Data mining, Data Mining is a decision support process. It is based primarily based on AI, machine learning, statistics, etc. Customer behavior, help companies' decision makers adjust market strategy, reduce risks, make correct decisions
CRM
Customer Relationship Management, data warehouse is based on database technology, but with traditional database applications, CRM is a new application based on data warehouse technology. However, from the perspective of business operation, CRM should actually be an old "application". For example, the hotel is managed by the guest information. If a guest is a hotel's old, then the hotel will naturally know some of the habits and preferences of the guest, if you like to rely on the road, do you smoke? Bed, what kind of breakfast like it, and so on. When the guest is temporarily, don't mention it yourself, the hotel will provide rooms and services like guests. This is a CRM.
Meta Data
Metadata, data on the data warehouse refers to key data related to data source definitions, target definitions, conversion rules, etc. in the data warehouse construction process. At the same time, metadata also contains business information about data, all of which should be properly saved and well managed. Provide convenient for development and use of data warehouses.
