Analysis of modern tools of intellectual analysis of cliometric data

Abstract

The article is devoted to the analysis of modern tools for creating an automated system for the intellectual analysis of cliometric data. Key technologies such as ETL tools, Big Data platforms (Hadoop, Spark, Kafka), NoSQL databases, cloud services (Google Cloud, AWS, Azure), as well as machine learning and artificial intelligence algorithms (in particular, neural networks) are considered. Particular attention is paid to the integration of technologies, automation of data processing, cleansing, visualisation and interpretation, as well as the role of expert systems in improving the quality of analytical results.