The Methods used before computers where introduced into healthcare is called Traditional methods use manual analysis to find patterns or extract knowledge from the database. For example in the case of health care, the health organizations (E.g. The Center for Disease Control in the US) analyze the trends in diseases and the occurrence rates. This helps health organizations take precautions in future in decision making and planning of health care management.
The traditional method is used to analyze the data manually for the models of knowledge extraction. Take any field of the area such as the Bank, the mechanical, the health and Marketing; there will always be a data analyst to work with the data and analyze the final results. The analyst
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It looks for hidden patterns among huge data sets that can help understand, predict and guide future behavior. A more technical explanation is: Data mining is the set of methodologies used to analyze data from various dimensions and perspectives, find previously unknown hidden models, classify and group data, and summarize identified relationships. The data extraction elements include data retrieval, transformation and loading into the data warehouse system, data management into a multidimensional database system, access to business analysts and experts computer, data analysis format, such as a chart or table. This is achieved by identifying the relationship using classes, clusters, associations, and sequential models via the use of statistical analysis, machine tilt and neural …show more content…
It is a valuable financial asset of a company. Companies can use data mining for knowledge discovery and exploration of available data. This can help them predict future trends, understand customer preferences and buying patterns, and conduct a constructive market analysis. They can then build models based on historical data models and draw more on targeted market campaigns and more profitable sales strategies. Data mining helps companies make informed business decisions, improves business intelligence, improving business revenue and reducing overhead costs. Data mining is also useful for finding patterns of data anomalies that are critical in detecting fraud and weak or incorrect data collection / modification areas. Getting help from data entry service providers experienced in the early stages of data management can facilitate subsequent data