ANALYTICAL METHODS USED IN BIG DATA

Abstract

The article defines the term "big data", identifies the features of big data, describes the methods of their analysis, reveals the differences between traditional data processing methods and big data technologies, determines the importance of using big data by enterprises. Big data has become a critical asset in modern organizations due to the rapid growth of digital technologies and data-generating systems. The ability to analyze large, complex, and diverse datasets enables organizations to extract valuable insights, improve decision-making processes, and gain competitive advantages. This paper explores key techniques for analyzing big data, including data mining, machine learning, statistical analysis, and distributed computing frameworks. The study highlights the importance of scalable and efficient analytical methods in handling the volume, velocity, and variety of big data. The findings emphasize how advanced analytical techniques contribute to predictive analytics, pattern recognition, and real-time data processing across various industries.