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Data Mining | Open Access Journals
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International Journal of Sensor Networks and Data Communications

ISSN: 2090-4886

Open Access

Data Mining

Data mining is the exploration and analysis of big data to discover meaningful patterns and rules. It is considered a discipline in the field of data science study and differs from predictive analytics in that it describes historical data, while data mining aims to predict future results. In addition, data mining techniques are used to create machine learning (ML) models that power modern artificial intelligence (AI) applications such as search engine algorithms and recommendation systems.
Data mining is a cornerstone of analysis, helping you develop models that can uncover connections in millions or billions of records. Many people learn how data mining is shaping the world we live in.
So why is data mining important? You have seen staggering numbers - the volume of data produced doubles every two years. Unstructured data alone represents 90% of the digital universe. But more information does not necessarily mean more knowledge.
Data mining lets you navigate through all the chaotic and repetitive noise of your data. Understand what is relevant and make good use of this information to assess likely outcomes. Accelerate the pace of informed decision making. Learn more about data mining techniques in data mining from A to Z, a document that shows how organizations can use predictive analytics and data mining to reveal new insights from data .

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Google Scholar citation report
Citations: 253

International Journal of Sensor Networks and Data Communications received 253 citations as per Google Scholar report

International Journal of Sensor Networks and Data Communications peer review process verified at publons

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