Big Data refers to extremely large, complex and varied data sets that require special tools and technologies for their effective storage, management, processing and analysis. The term "big data" refers not only to the size of the data, but also to the speed of data generation and the variety of data types and formats.
The modern concept of Big data appeared in the McKensey report: Big data: The next frontier of innovation, competition and productivity..
Big Data processing and analysis often involves the use of advanced artificial intelligence and machine learning techniques, as well as distributed systems and scalable storage technologies to handle large volumes of data in real time. Some of the key challenges in Big Data analytics include integrating data from multiple sources, identifying meaningful patterns and trends, and managing data privacy and security.
Applications of Big Data include data mining, business intelligence, social network analysis, search engine optimisation, data science and data-driven decision making. Examples of datasets that are considered Big Data include sensor datasets, financial transactions, web activity logs, phone call logs, social media data, and healthcare records.
Clustering methods, or grouping, are a fundamental part of the data analysis process, since they allow an automatic segmentation of the data [...]
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