USE OF EXCEL STATISTICAL FUNCTIONS IN ANALYTICAL RESEARCH OF BIG DATA
Abstract
The article examines the specifics of using Excel's statistical functions in conducting analytical studies of big data. Basic Excel statistical functions such as arithmetic mean, median, variance, standard deviation, and others are covered. The specifics of using these functions for analyzing big data in various fields and business processes, including finance, economics, marketing research, etc., have been studied. Methods of data summarization, filtering, sorting and use of tables of contents for fast and efficient analysis of large data sets are considered. The advantages and limitations of using Excel for big data analytics are explored. Alternative tools and programs for big data analysis are considered. Based on the conducted research, it was determined that Excel is a powerful tool for data analysis in various areas of economic analytics, including for working with Big Data. Limitations of the program that can affect the accuracy and speed of processing large volumes of data have been identified. It is recommended to consider such limitations in the analysis process and consider alternative means of processing big data depending on the specific needs of the study. The use of Excel statistical functions in analytical studies of big data becomes especially relevant in modern economic analysis, where data volumes are constantly and dynamically growing and becoming extremely large in volume. At the same time, Big Data plays a key role in various fields, including scientific research, technology, business processes, medicine, and others. At the same time, in recent years, the pace of data growth has become a significant challenge for analysts and researchers in all fields. Processing and analysis of large volumes of data require powerful tools and specific analysis methods that would ensure accuracy, speed and efficiency of analytical processes. In this aspect, Excel, as one of the most common software products for data analysis, has powerful statistical functions that can be used for Big Data analytical research. However, it is known that Excel has certain limitations regarding the amount of data that can be processed, and there may also be a problem with the performance of the software application itself when working with large data sets.
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