Usage of Big Data for Information Support of the Labor Market

Mykhailo Rozbytskyi
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Abstract

The challenges of collecting current labor market data amidst global changes and geopolitical fluctuations increasingly necessitate new approaches and alternative methods of data collection and analysis. This highlights the relevance of research aimed at developing and adapting labor market information provision methods to contemporary challenges. A promising approach in this context is the use of Big Data for labor market assessment, which involves collecting information from sources such as online job search and vacancy portals. This method allows for a deeper analysis of market trends and provides a more accurate and timely assessment of labor market needs and opportunities. The aim of this article is to discuss approaches to developing labor market information systems using Big Data, particularly online data from job vacancy websites. It examines the use of Big Data in labor market analysis based on a database containing over four million job vacancies posted on Ukrainian job search portals over the last five years, provided by the European Training Foundation (ETF). The effectiveness of these approaches in facilitating job search for all interested parties is evaluated, particularly through providing insights into the dynamics of supply and demand in the labor market based on data from these portals. The opportunities and limitations of using Big Data in this context are analyzed, including their impact on employment policy development and labor market planning. The potential benefits of Big Data in providing deeper and more accurate market condition analyses are outlined, along with technical aspects and challenges associated with their processing and interpretation. The article examines methodological approaches to data collection and analytical processing in the context of accelerated transformations, volatility, and limited access to traditional information resources. The scientific novelty of the article lies in the substantiation of the feasibility and appropriateness of using open data from online job portals for labor market information provision under current conditions. In conducting the research, methods of analysis, synthesis, and generalization were applied to identify the main contemporary issues of labor market information provision in Ukraine. The effectiveness of data collection methods based on web scraping and parsing techniques was evaluated, as well as the use of the integrated Snowflake platform to identify key trends and patterns in the labor market. The conclusions summarize the main points and substantiate directions for further research, highlighting the significance of Big Data in developing employment strategies and optimizing the labor market.
利用大数据为劳动力市场提供信息支持
在全球变化和地缘政治波动中收集当前劳动力市场数据所面临的挑战日益需要新的数据收集和分析方法和替代方法。这凸显了旨在开发和调整劳动力市场信息提供方法以应对当代挑战的研究的相关性。在此背景下,一种很有前途的方法是将大数据用于劳动力市场评估,这涉及从在线求职和空缺职位门户网站等来源收集信息。这种方法可以对市场趋势进行更深入的分析,并对劳动力市场的需求和机会进行更准确、更及时的评估。本文旨在讨论利用大数据开发劳动力市场信息系统的方法,特别是来自职位空缺网站的在线数据。文章以欧洲培训基金会(ETF)提供的一个数据库为基础,研究了大数据在劳动力市场分析中的应用,该数据库包含乌克兰求职门户网站在过去五年中发布的四百多万个职位空缺。评估了这些方法在促进所有相关方求职方面的有效性,特别是通过基于这些门户网站的数据对劳动力市场供需动态的深入了解。分析了在此背景下使用大数据的机遇和局限性,包括其对就业政策制定和劳动力市场规划的影响。文章概述了大数据在提供更深入、更准确的市场状况分析方面的潜在优势,以及与数据处理和解释相关的技术问题和挑战。文章探讨了在加速转型、不稳定性和传统信息资源获取途径有限的背景下,数据收集和分析处理的方法论。文章的科学新颖性在于论证了在当前条件下利用在线招聘门户网站的开放数据提供劳动力市场信息的可行性和适宜性。在研究过程中,运用了分析、综合和概括的方法来确定乌克兰劳动力市场信息提供的主要当代问题。评估了基于网络刮擦和解析技术的数据收集方法的有效性,以及使用集成的 Snowflake 平台确定劳动力市场主要趋势和模式的有效性。结论总结了要点并证实了进一步研究的方向,强调了大数据在制定就业战略和优化劳动力市场方面的重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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