Current Aspects of the Data Ecosystems

Abstract

Current trends and future developments in the field of data storage, processing, analysis, output, and visualization include various possible directions and future developments of these systems. This paper discusses the current state of data ecosystems and possible future developments based on an analysis of publications and studies from the last time. Commonly known trends point to approaches that enable more efficient data management, faster data analysis and, of course, the integration of different types of data coming from different sources. Additionally, the study evaluates the ETL process performance, identifying key metrics, optimizations, and bottlenecks in data processing workflows. The benefits and development of generative models are also changing the way we work with data, with implications for improved visualizations and general process automation. Thus, in the area of analysis, it can be assumed there will be an even greater emphasis on interactive and intuitive reports that make it as easy as possible to understand complex data structures. In terms of the use of system resources, the use of Cloud services is the basis for the comprehensive use of scalability and flexibility at lower infrastructure costs. Another area that the paper discusses is the current growing demand for real-time data analysis due to the increasing need for quick decisions based on data evaluation.