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SUKD2002013

Data mining is the process of identifying patterns in massive data sets using techniques that combine machine learning, statistics, and other disciplines. It makes use of huge data, sophisticated computing techniques, including machine learning and other artificial intelligence techniques (Al). Finding patterns in otherwise unstructured or huge data sets that can be used to draw conclusions or make predictions is the objective.

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CHENYIHENG  SUKD1802314
Data mining refers to the process of searching for information hidden in a large amount of data through algorithms.
Data mining is often associated with computer science and uses statistics, online analytical processing, intelligence retrieval, machine learning, expert systems (relying on past rules of thumb), and pattern recognition to achieve these goals

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SUKD2101996
WHAT IS DATA MINING?

Data mining is the process of sorting through large data sets to identify patterns and relationships that can help solve business problems through data analysis.

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Data mining is a key area of data science and a crucial part of data analytics as a whole, which uses complex analytics techniques to find informational content in data sets. Huge data sets are sorted using a method called data mining in order to discover patterns and relationships that may be utilised to address business challenges through data analysis.

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Large data sets are sorted through in data mining in order to find patterns and relationships that may be used in data analysis to assist solve business challenges. Enterprises can forecast future trends and make more educated business decisions thanks to data mining techniques and technologies.

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Data mining is most commonly defined as the process of using computers and automation to search large sets of data for patterns and trends, turning those findings into business insights and predictions. Data mining goes beyond the search process, as it uses data to evaluate future probabilities and develop actionable analyses.

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What is Data Mining?
Data mining is the process of extracting and discovering patterns in large data sets using methods from machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with the overall goal of extracting information (using intelligent methods) from a data set and transforming the information into a comprehensible structure for further use.

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sukd2001620

data mining is an important aspect of analysis and data sciences, it uses data sets to extract crucial informatio via analytic techniques.

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Data mining, also known as knowledge discovery in data (KDD), is a process of discovering patterns and other valuable information from large data sets. In view of the development of data warehouse technology and the growth of big data, the adoption of data mining technology has accelerated rapidly in the past few decades, assisting the company by transforming raw data into useful knowledge. However, although the technology continues to evolve to handle data on a large scale, leaders still face challenges in scalability and automation.

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SUKD1901807
Data mining is a key part of data analytics overall and one of the core disciplines in data science, which uses advanced analytics techniques to find useful information in data sets. Data mining is a process used by companies to turn raw data into useful information.

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SUKD2001742
Data mining is a key step of knowledge discovery, which refers to automatically searching the data and information hidden in a large amount of data with special relationships and transforming them into a structured representation that can be processed by computers. The generalized view of data mining: the complex process of extracting implicit, previously unknown, potentially useful knowledge such as models or rules from a database is a kind of deep data analysis method. Data mining is a comprehensive technology, involving the synthesis of statistics, database technology and artificial intelligence technology, its most important value is to use data mining technology to improve the prediction model.

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Data mining is the result of a long history of research and development of database technology. Originally, various business data were stored in databases in computers, and then evolved to the ability to query and access databases, and then to instant traversal of databases. Data mining brings database technology to a more advanced stage, not only querying and traversing past data, but also identifying potential links between past data to facilitate the transfer of information.

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Data mining is most commonly defined as the process of using computers and automation to search large sets of data for patterns and trends, turning those findings into business insights and predictions. Data mining goes beyond the search process, as it uses data to evaluate future probabilities and develop actionable analyses

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Data mining is often associated with computer science and uses statistics, online analytical processing, intelligence retrieval, machine learning, expert systems (relying on past rules of thumb), and pattern recognition to achieve these goals. There is a huge amount of data out there that is widely available, and there is an urgent need to transform that data into useful information and knowledge. The information and knowledge gained can be used in a wide range of applications, including business management, production control, market analysis, engineering design and scientific exploration.

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sukd2001997 gaohaorun is the process of uncovering patterns and other valuable information from large data sets. 

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sukd2001997 gaohaorun is the process of uncovering patterns and other valuable information from large data sets. 

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Nyeo Siang Ping                                        SUKD2200197

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Nyeo Siang Ping                                        SUKD2200197

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Finding anomalies, trends, and correlations within huge data sets in order to forecast outcomes is known as data mining. Using a variety of strategies, you may utilize this knowledge to raise profits, lower expenses, strengthen bonds with clients, lower risks, and do much more.

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Data mining is the process of analyzing massive volumes of data to discover business intelligence that can help companies solve problems, mitigate risks, and seize new opportunities. This branch of data science derives its name from the similarities between the process of searching through large datasets for valuable information and the process of mining a mountain for precious metals, stones, and ore. Both processes require sifting through tremendous amounts of raw material to find hidden value.

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Data mining is an umbrella term in the data science field, is the process of sorting large data sets to identify patterns within and establish inter-relationships to solve problems through data analysis. Data mining is the discovery of interesting, unexpected or valuable structures in large datasets.

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Data mining improves organizational decision making through insightful data analysis.
Data mining is the process of extracting and discovering patterns in large data sets, involving a cross-cutting approach to machine learning

Data mining improves organizational decision making through insightful data analysis.

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Data mining is the process of sorting large data sets to identify patterns and relationships that can help solve business problems through data analysis. Data mining is a technique and tool that allows people to predict future trends in an business to make more informed business decisions.

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Data Mining is to analyzing dense volumes of data to find patterns, discover trends, and gain insight into how that data can be used for example like the supermarket concept that use  collaborative purchasing patterns to identify the product associations and decide how to place them in the aisles and on the shelves.

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What is Data Mining?

There is a long history of sifting through data to find hidden relationships and forecast upcoming trends. Ninety percent of the digital cosmos is made up exclusively of unstructured data.