ZT: Data Warehouse FAQ
Data Warehouse defines the concept of data warehouses in its "Father of Data Warehouse", "Data Warehouse", which is defined in its "establishing data warehouse" book, and then gives a more accurate definition: Data warehouse is In business management and decision-oriented, integrated, time-related, invisible data collection. 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.
The concept of OLAP Online Analysis (OLAP) was earliered by the Father 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 multi-dimensional conceptual view guidelines 2 Transparent guidelines 3 Access capacity estiminal 4 Stable report capability criteria 5 Customer / Server Architecture guidelines 6D equivalence criteria criteria 7 Dynamic sparse matrix treatment guidelines 8 Multi-user support capability guidelines 9 Non-restricted cross-dimensional operation criteria 10 intuitive data manipulatory criteria 11 Flexible report generation criteria 12 Unrestricted dimensional aggregation hierarchical 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.
MOLAPARBOR SOFTWARE strictly follows the CODD definition, and the multi-dimensional database is created, and the online analysis system data has created the first river of cube, 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 is 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 (DISION Support System) is equivalent to a data warehouse based application. 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, the most common query, database application, using data warehouse technology, allows users to facilitate the database to get the desired data.
EIS Leading Information System, refers to an application that visits data warehouses in a simple graphical interface in order to meet the information query requirements that cannot focus on leaders of computer technology.
BPR Business Process Rengineering, one of the important roles of data warehouses using data warehouse technology, discovery and correcting the drawing of corporate business processes.
Bi Business Intelligence, Index Name of Stained Technology and Application. 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, which is based primarily based on AI, machine learning, statistics, etc., highly automatedly analyzes the original data of enterprises, and makes the inductive reasoning, and digs potential patterns. , Predict the behavior of customers, help companies' decision makers adjust market strategies, reduce risks, and 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.
