Types of IP and the principles of their creation
As classification characteristics of IP are highlighted the most significant features, such as the parameters of the object management (scope, scale, composition of the management function); organizational form of IP; level of integration of IP functions and data; information technology architecture of IP; technological processes of data processing; IP methodology, etc. Below is a list of similar features:
1. The scope of the management object: industrial enterprise: the sphere of circulation (trade, banks and credit organizations); education; social sphere, etc.
2. Functional structure of IS: automation of technical preparation of production; marketing and enterprise development strategy; technical and economic planning; finance (accounting, financial analysis); material and technical support; operative calendar production management; sales management of finished products; personnel management, etc.
3. Organizational structure of IP: automated workplace for management personnel (AWP); a complex of interconnected workstations.
4. Levels of IP use: enterprise (organization) IP; Industry IP; state IP; international IS.
5. Degree of integration of IS: local IS (isolated information space); partially integrated information system (general information space); fully integrated enterprise IP.
6. Information and technological architecture of IS: AND With a centralized architecture of construction (one data storage and processing center); IS distributed architecture (computer networks, the existence of multiple processing centers and information storage).
7. IP specialization: management IP (otherwise, organizational and economic management) - Information Management System, IMS; information retrieval systems - Information Retrieval System, IRS; the system of automated training - Education Information System, EIS, etc.
The most common are management IP, among which are: Enterprise Resource Planning - ERP (CIS - Corporate Information Systems); Real-Time Systems - RTS (real-time management systems, including automated process control systems - automated control systems for technological processes and industries); Product Lifecycle Management - PLM (product lifecycle management systems, including: CAD-systems (Computer-Aided Design) - computer support for design; CAM-systems (Computer-Aided Manufacturing) - computer manufacturing support; CAE-systems (Computer- Aided Engineering) - support engineering calculations), etc.
The Management Information System (ERP) as components includes other specialized ICs for Office Automation System (OAS), Decision Support System (DSS), Knowledge Management System (KBS) and others
Special decision support systems are created for the development of the enterprise development strategy (perspective directions, planning, investment design, etc.), using methods of statistical analysis and forecasting, data modeling and business processes, simulation modeling, so-called corporate strategic systems - ESS (Enterprise Strategic System). In the decision support IPA, OLAP technologies (On-Line Analytical Process - operational analysis and processing of data obtained from data warehouses (Data Warehouse - DW), data extraction technology (DataMining - DM), information extraction technology from the text TextMining - TM) and modeling of business processes.
In modern and management is significant role and EIC artificial intelligence - AIS (Artificial Intelligence System). These ICs support a natural language interface for users (specialists in the formalization of knowledge), provide methods of artificial intelligence for solving poorly structured and poorly formalized problems. The AIS core is the knowledge base (KB) that is used to generate new information by inference. To represent the economic object and its environment, to study its behavior and reactions to external events, mathematical modeling, means of deductive and plausible conclusions derived from incomplete or inaccurate information are applied. Among the AIS, the expert systems (ES) are the most widely used, with the help of which a hypothesis is advanced and evaluated on the basis of real data. Other examples of AIS: full-text search ICs (combined with relational DBMSs (RDBMS), form a new class of post-relational DBMS); neural networks; IS of analytical calculations based on methods of operations research, mathematical modeling, statistical analysis and forecasting, etc.