ETL TECHNOLOGY AS AN APPROACH TO DATA INTEGRATION

This article is devoted to the study of the corporate data integration problem. The aim of the work is the analysis of the existing ways of big data integration and implementation of a software system that allows the implementation of the full cycle of data extraction, transformation, and load (ETL). Most of the information required for analytical applications stored in the corporate management systems, databases and individual user files. Data integration tools provide the necessary infrastructure for converting disparate data sources into a single resource. When the company starts an integrated enterprise data warehouse (EDW) development, the number of data streams increases many times. For efficient use of EDW, it requires data on all aspects of the enterprise operations and the transfer of large volumes of detailed data from each source system to the warehouse. The main problem of data integration is the use of a large number of tools and technologies for solving integration problems in organizations. However, the effectiveness of such solutions drops with an increase in data streams quantity. In order to ensure effective integration, tools that can provide a general overview and management of all data flows are needed. Tools for integration should work equally effective with all DBMS used by the organization, data sources, messaging systems, etc. The integration method developed and presented in the article is designed for small enterprises that work with large data volumes that require low cost, easy to deploy and scale solutions. The features of work with data for small enterprises were investigated. Based on them, the requirements for the input data, as well as methods of their filtration and cleaning are formulated. The result of the work is a developed algorithm and data loading procedure into a prepared data warehouse.