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Big Data

"Big Data" is the area of analyzing, extracting systematically, or processing, data sets that are too large or complex to consider with traditional data processing software. Data in many cases (rows) provide more statistical power, while data with higher complexity (more attributes or columns) can cause higher false detection rates. The main data acquisition challenges include data collection, data storage, data analysis, searching, sharing, transfer, visualization, requests, updates, confidentiality of information, and data sources. Initially Big Data refers to three main concepts: volume, variation and speed. When we process big data, we may not take samples, only monitor and track what happens. For this reason, big data often includes data of a size that exceeds the capacity of conventional processing software in an acceptable amount of time and value.

The current use of the term big data usually refers to the use of predictive analytics, user behavior analysis, or other modern data analysis methods that extract values from data and rarely to a certain size of record. "There is no doubt that the data already available is actually large, but that is not the most relevant feature of this new data ecosystem." Fight crime, etc. "Scientists, business leaders, medical professionals, advertisers, and governments routinely face difficulties with large amounts of data in areas such as internet research, fintech, and urban and business computing. Scientists face limitations in electronic work, including meteorology, genomics, connectometry, complex physical simulations, biology, and environmental studies.

Big data analysis is often a complex process of looking at large and diverse amounts of data or big data for hidden disclosure patterns, unknown correlations, market trends, and customer preferences - which help companies make informed business decisions.

Data analysis technology and methods provide great opportunities to analyze and draw conclusions from data sets to help companies make informed business decisions. Business intelligence questions (BI) answer the questions of basic business processes and efficiency.

Big data analysis is a form of complex analysis involving complex applications with elements such as predictive models, statistical algorithms, and usage analysis with high performance analysis systems.

Led by specialized analysis systems and software, as well as powerful computer systems, Big Data Analysis offers several business benefits, including:

Big data analytics applications allow big data analysts, data scientists, forecasting models, statisticians and other analysts to analyze the growing volume of structured transaction data and other types of data that are often not used by traditional BI and analytic programs. This includes a combination of semi-structured and unstructured data such as click-to-play Internet data, web server logs, social media content, text from customer emails and survey responses, cellphone records, and machine data collected by sensors. Internet of Things (IoT).