1. Data Center
1. Concept: As applications continue to move closer to the server side and Internet services are widely popularized, a new computing system emerges, which is called data center, also known as warehouse-level computing.
2. Features:
Data centers focus on cost-effectiveness. A
data center is essentially a collection of many servers that run programs as a unified computing unit (how to design the system architecture is the key to building a data center).
One data center or multiple data centers
3. Data center The evolution of
data center development stage
1945~1971 mainframe era
1971~1995 Minicomputer era
1995~2005 Internet Era
2005~Today's Cloud Era
Future development trend of data center
Highly virtualized
Green , environmentally friendly, low carbon
Container and modular
Cloud data center
4. Hierarchical data center Tier 1 data center: separate paths for
power and cooling, no backup components
Add some backup components to improve availability
Tier 3 data center: has multiple paths for power and cooling distribution, but only one active path.
Tier 4 data centers: have two active power and cooling paths, and provide backup components for each path, thus avoiding a single point of failure without affecting the load.
5. Data center architecture
Introduction , storage, network structure, data hierarchy, (quantitative description of delay, bandwidth, capacity), energy utilization, fault handling
II. Data warehouse
1. As an information management technology, data warehouse can Various data distributed in the enterprise are reprocessed to form a comprehensive and analysis-oriented environment to better provide various effective data analysis for decision makers and play a role in decision support. It also reduces system burden, simplifies routine maintenance and management, improves data integrity, and provides users with a simple and unified query and reporting mechanism.
2. Features:
The data in the data warehouse is organized by subject.
The data in the data warehouse is integrated.
The data in the data warehouse is stable.
The data of the data warehouse is constantly changing with time
3. The difference between the data warehouse and the database
In terms of physical implementation, there is no essential difference between a data warehouse and a database in the traditional sense, and it is mainly implemented in the form of relational tables.
4. Organizational structure of data warehouse data
The data of the data warehouse is divided into four levels: early detail level, current detail level, light comprehensive level, and high comprehensive level.
"Granularity": There are different levels of synthesis in a data warehouse. The larger the granularity, the lower the level of detail and the higher the level of synthesis.
Metadata: data metadata, business metadata
5. Data warehouse architecture
(1) The data source is the basis of the data warehouse system and the data source of the entire system, usually including enterprise internal information and external information.
(2) The storage and management of data is the core of the entire data warehouse system.
(3) The OLAP server effectively integrates the data required for analysis and organizes it according to a multi-dimensional model, so as to conduct multi-angle and multi-level analysis and discover trends.
(4) Composition of front-end tools