Talking about the Application of Data Warehouse Technology in Printing Enterprises
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With China's accession to the WTO and the increasing degree of global informationization, it has brought great development opportunities and huge challenges to the printing industry. In an era of fierce competition, how do printing companies win in many enterprises; in today's information age, who can more effectively mine core information resources in massive information, thus providing more management for business managers The decision-making reference for value is worthy of attention.
At present, we have established various application subsystems in many printing companies, such as customer business subsystem, production subsystem, financial subsystem, sales subsystem, etc., which can still be used to some extent in their respective fields. Satisfying demand, here is when the analysis process involves only a small amount of data information. Database systems for frequent operational processing are often overwhelmed when the amount of data grows rapidly and query requirements continue to become more complex. Therefore, a new technology must be adopted to enable complex analysis and processing, so data warehouse technology came into being.
First, data warehouse technology
Data warehouse technology appeared in the 1980s. In the 1990s, the famous American engineering scientist Dr. W. H. Inmor gave the definition of data warehouse: data warehouse is subject-oriented, integrated, and non-renewable (stability A collection of data that changes over time (including historical data at different times) to support the decision-making process in business management. It is an enterprise information management solution that is a system architecture, not a software product or application. The data warehouse architecture integrates business data distributed across various structured databases at different sites in the enterprise network and is at the heart of a decision support system environment based on large-scale databases. It is a relatively effective solution to solve the problem of too much data in the management and decision-making activities of the enterprise but lack of useful information.
1. Data warehouse features
Unlike a dedicated database, a data warehouse has the following characteristics:
1.1 Data warehouse is subject-oriented. It takes the main content of business work as the main line, obtains effective information data from a large number of scattered private databases, physically partitions according to the subject area, transforms and organizes them into new storage systems, and aggregates data in In the new special structure, and establish the link relationship of each subject area. It should be said that the subject is the standard for data acquisition and categorization in data warehousing.
1.2 Integration is an important feature of data warehousing. Data warehouse data comes from different application systems, using different data structures and types, with different encoding methods. Therefore, it is not possible to simply copy each detail data, but to process the data and unify different types of data into the data warehouse model. Data integration is a crucial link in the construction of data warehouse.
1.3 Changes over time are another feature of data warehousing. Generally, the dedicated database only stores the currently running application system data, and the other time data is only used as backup storage, and there is no connection before or after. Data warehouse data is often used as a trend analysis, and it needs to have enough historical data, and the time span can be very long. Temporality is an inevitable requirement of data warehouses for analyzing the inherent laws of data.
Another feature of the 4 data warehouse is the non-volatility (ie, stability) of the data. The data of the data warehouse is the analysis data for comprehensive processing of a certain topic. Once the data is formed and loaded into the data warehouse, in principle, the management personnel are not allowed to change or delete at will, and can only be periodically refreshed.
2. The composition of the data warehouse system
Data warehousing technology is actually an information integration technology. The data warehouse obtains raw data from a variety of information sources, and then stores them in an internal database of the data warehouse. Then, through the access tool, the user is provided with integrated information to help the business manager conduct in-depth and comprehensive analysis to support the overall decision of the enterprise. Based on these needs, a data warehouse generally includes the following parts:
2.1 data source: provide source data for the data warehouse, such as business database, production database, and so on.
2.2 data extraction, transformation and loading tools: extract data from the data source, then reorganize the processing, loading into the target database.
2.3 data modeling tools: establish an information model for the source database and the target database.
2.4 core warehousing: store data models and metadata.
2.5 target database: store data that has been verified, organized, processed, and reorganized.
2.6 Front-end data access and analysis tools: Enterprise decision makers and business analysts use these tools to further analyze data in the target database.
2.7 data warehouse management tools: provide management tools for the operation of data warehouse, such as security management, storage management.
Second, the data warehouse module in the printing industry
At present, in most enterprises, the establishment of data warehouse is mainly based on the business theme for data integration, and the printing enterprise is the same. According to the characteristics of the printing industry, the current printing enterprise data warehouse mainly includes the following modules according to the theme:
1 Customer Analysis Module: It mainly analyzes the type and composition of customers, finds core customers and valuable customers based on past business distribution, and finally analyzes the key factors affecting business volume. Through this module, companies can clearly analyze the market prospects and establish a good mutual trust mechanism with customers.
2 Production management analysis module: systematically analyze the whole production process, mainly from the aspects of production efficiency analysis, reasonable arrangement of various departments, efficiency trend analysis, etc., so as to help managers master production and operation situation and influence production. The key factors, and then the corresponding solution to the problem, in order to improve the company's production efficiency and management level.
3 Order Business Analysis Module: As a special industry printing industry, it does not provide sales work itself, and it is produced according to the order. Therefore, the analysis of the order is very important, mainly from the order type, business volume, regional distribution, customer, documentary situation and printing methods, etc., and then explore the business volume of the company in recent years, analysis The change in business volume and the main influencing factors, thus accurately reflecting market trends and making correct decisions for the further development of enterprises.
4 Logistics management analysis module: This mainly analyzes the aspects of purchase, inventory, shipment, material utilization, transportation cost, distribution cost, etc., and obtains the main aspects that affect the cost, and establishes relevant improvement systems in time to improve the efficiency of the enterprise.
In addition, there are modules such as financial analysis and personnel analysis, which are determined according to the specific conditions of the company. In addition to these analysis modules in the data warehouse, there must be corresponding fact tables, such as customer data fact tables, quotation management fact tables, and so on.
Third, the establishment of printing enterprise data warehouse
Establishing a data warehouse in a printing company, like other industries, must follow the following principles:
1 Step-by-step principle: Building a data warehouse with large investment, high risk, and long time can't be done overnight. Don't expect to build a huge global data warehouse from the beginning. From the small, well-defined, and data-contrast themes, from simple to complex, from local to global, implemented in stages.
2 The principle of scalability: The size of the data warehouse expands with the expansion of the subject area, and on a certain topic, it also changes dynamically as the data increases. Therefore, building a data warehouse must demonstrate scalability in terms of data architecture, data storage, and data processing.
3 Practicality principle: The structure of the data warehouse is driven by business needs and integrates data according to business themes.
Building a data warehouse in the current printing enterprise does not use the traditional lifecycle approach, but instead employs a rapid development approach similar to the rapid prototyping approach. After determining the topics such as order business, customer, production, etc., the enterprise conducts investigation and analysis, and then builds a mathematical model (generally a star model) based on the original various subsystem data, and directly establishes a data warehouse. And realize the system prototype for the user to try and use the information in time; then the company will gradually adjust the system prototype according to the feedback information to make it gradually perfect and provide more satisfactory decision-making services for the manager. This data warehouse system is built under a new architecture with comprehensive development tools to meet the needs of various users in a timely manner.