CC BY
3IN INTEGRATION OF INFORMATION SYSTEMS ANALYSIS OF AVAILABLE
METHODS AND PROBLEMS
Y.N.9LiYEVA, M.K.NÎYAZLI
Azerbaijan State Oil and Industry University
Abstract: In the article, the concept of integration of Information Systems, its importance, the activities carried out for the integration of Information Systems were examined. The companies applying the integration of Information Systems and the profits they get through this system have been studied.
Keywords: Information, Information Systems, integration, XWiki, YouTrack
Introduction. Integration of information systems is necessary to maintain the integrity of distributed information. IS integration is the process of establishing links between information systems of enterprises in order to obtain a single information space and organize support for business processes.
Today, there are a huge number of such tools that directly and indirectly solve the problem of planning and tracking work on a project, with varying degrees of efficiency, but the future belongs to products that integrate not only tools for entering, sorting, presenting and formatting data, but also containing analytics tools, programming and search [1].
This work is part of an overall project to integrate XWiki and YouTrack systems, reflecting the interaction between XWiki and a web service. The work will use the materials presented in the design of the interaction between YouTrack and the web service, where the web service is a common intermediary in the integration of project systems.
Materials & Methods. Information integration refers to the integration of data located in multiple systems, and their presentation in a unified, consistent and accurate form, which is intended for the study and processing of data. This integration is intended solely for end users who need to work with multiple systems to complete their tasks.
A prerequisite for the implementation of data integration is a thorough analysis, firstly, of the systems and data involved, in order to determine the relevant data that is subject to extraction and transformation procedures and secondly, the target structures into which this data will be loaded. Reporting is carried out using analytical tools that allow you to take a fresh look at the collected data every time, i.e. help create the information needed to make decisions.
Depending on the system, the data may be presented in different formats and with different labels that are most appropriate for their use, and therefore the user will have to correlate them in order for the data to be usable. Thus, duplicate and unreliable data may arise, which affects the quality of the information.
Information quality problems occur in individual datasets such as files and databases, for example, as a result of input errors, loss of information and other data contamination. When multiple data sources are to be integrated in integrated database systems or global Internet information systems, the need for data cleansing is increasing significantly. This is because sources often contain disparate data in different representation. To ensure access to accurate and consistent data, it is necessary to consolidate various data representations and eliminate duplicate information [2].
Databases are loaded and constantly updated with huge amounts of data from various sources, so the probability of getting into them "dirty data" is very high. Moreover, integrated information systems are used for decision-making, therefore, it is necessary to make adjustments to the downloaded data, since duplicate or lost information can cause incorrect or inadequate statistics. Due to the wide range of possible inconsistencies in the data and the large volume of data, cleaning them is considered one of the biggest problems in data integration technology. All data cleaning is usually done in a separate data staging area before the converted data is uploaded to the end user.
Data transformation is required to support any change in the structure, presentation, or content of the data. These transformations become necessary when changing the data structure, moving to a new information system, or when you need to integrate multiple data sources.
The problems presented in individual sources are exacerbated when multiple data sources are integrated. Each source can contain contaminated data, as well as data presented in different ways, overlapping and contradicting each other. The reason for this is usually independent development, implementation and support of sources, focused on the specific needs of enterprises. As a result, 22 there is considerable heterogeneity in data management systems, data models, circuit designs, and current data.
The main problem of integrating data from multiple sources is the identification of overlapping data, in particular, matching data related to the same object of the real environment. This problem is also called the problem object identity, the problem of avoiding duplication. Often the information is redundant only in places and sources can complement each other, providing more complete information about the object. Of course, duplicate information should be removed, but complementary information must be consolidated and connected so that the objects of the real environment receive a consistent view.
In conclusion, the main problems of data source integration can be identified - these are name conflicts and structural conflicts at the database schema level, and at the data element level, different representations of information and duplicate records can be observed. Solving these problems requires both schema integration and data cleansing. To do this, first of all, schema conflicts must be resolved in order to ensure the possibility of data cleaning, in particular, the identification of duplicates based on a unified presentation of information. [3]
Analysis of existing methods of information systems integration
An information system is a combination of several components, therefore, speaking about the integration of information systems, one should mean the integration of their constituent components. Typically, an information system contains the following components, shown in Figure 1.1:
• The platform on which the other components of the system operate, including hardware (hardware) and system software;
• The data the system works with. Consist of DBMS and databases;
• Applications that implement the business logic for working with the given system. They consist of business logic components, a user interface, auxiliary components (framework) and an application server that provides storage and access to application components;
• Business processes, which are scenarios for how users work with the system.
Figure 1.1 - The main components of information systems
Conclusion. As a result, the integration of information systems is the integration of one or more components of the integrated information systems (integration objects).
LITERATURE REVIEW
1. Information integration Standard Requirements Paperback by Gerardus Blokdyk -October 29, 2021
2. Developing Data Migrations and Integrations with Salesforce: Patterns and Best Practices 1st ed. Edition, Kindle Edition by David Masri - December 18, 2018
3. Design and Verification of Information Integration Architecture: Design Of Comprehensive Service-oriented Information Integration Architecture
by Punitha Devi C (Author), Prasanna Venkatesan V (Author) - July 17, 2020
4. The Data Integration Guide: How to design, deliver, deploy, and sustain efficient data integration solutions in your information system by Ahmed Fess - June 16, 2022
5. «О XWiki» // https://habr.com/post/265811/ (Дата обращения 29.01.2019).
6. «Проблемы интеграции» // http://ict.informika.ru/ vconf/files/10137.pdf (Дата обращения 17.02.2019).
