Data Mining
What is Data Mining
Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
Continuous Innovation
Although data mining is a relatively new term, the technology is not. Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research reports for years. However, continuous innovations in computer processing power, disk storage, and statistical software are dramatically increasing the accuracy of analysis while driving down the cost.
In the Process Industries, similarly, data and text mining operations can be performed on huge volumes of real time data stored in a historian (i.e. OSIsoft PI system).
Data, Information, and Knowledge Data
Data are any facts, numbers, or text that can be processed by a computer. Today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes:
1) Operational or transactional data such as, sales, cost, inventory, payroll, and accounting
2) Nonoperational data, such as industry sales, forecast data, and macro economic data
3) Meta data - data about the data itself, such as logical database design or data dictionary definitions
Information
The patterns, associations, or relationships among all this data can provide information. For example, analysis of retail point of sale transaction data can yield information on which products are selling and when.
Benefits Data Mining: Knowledge for Proactive Decision Making
Data Mining can turn data into information, and information into knowledge about historical patterns and future trends. From retail sales to customer credit scoring in the business sectors and from plant performance analysis to prediction of asset performance or failure, data mining can deliver the knowledge needed to make your business a proactive operation.
What can data mining do?
Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.
In the case of the Process Industries, dat mining can be applied to process data to enable root cause analysis, development of multi-variate - based control applications for advanced process control and prediction of measured or non-measured variables.
Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.
Continuous Innovation
Although data mining is a relatively new term, the technology is not. Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research reports for years. However, continuous innovations in computer processing power, disk storage, and statistical software are dramatically increasing the accuracy of analysis while driving down the cost.
In the Process Industries, similarly, data and text mining operations can be performed on huge volumes of real time data stored in a historian (i.e. OSIsoft PI system).
Data, Information, and Knowledge Data
Data are any facts, numbers, or text that can be processed by a computer. Today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes:
1) Operational or transactional data such as, sales, cost, inventory, payroll, and accounting
2) Nonoperational data, such as industry sales, forecast data, and macro economic data
3) Meta data - data about the data itself, such as logical database design or data dictionary definitions
Information
The patterns, associations, or relationships among all this data can provide information. For example, analysis of retail point of sale transaction data can yield information on which products are selling and when.
Benefits Data Mining: Knowledge for Proactive Decision Making
Data Mining can turn data into information, and information into knowledge about historical patterns and future trends. From retail sales to customer credit scoring in the business sectors and from plant performance analysis to prediction of asset performance or failure, data mining can deliver the knowledge needed to make your business a proactive operation.
What can data mining do?
Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data.
In the case of the Process Industries, dat mining can be applied to process data to enable root cause analysis, development of multi-variate - based control applications for advanced process control and prediction of measured or non-measured variables.
