What is data mining?
Data mining is also referred to as knowledge discovery and is defined as the process of analyzing data from different sources and perspective and summing it up into useful information. This information can be used in many ways including to cut costs and increasing revenue.
Technically, data mining is defined as the process of identifying patterns and correlations in large data. Data mining software is one of the many analytical tools that can be used in analyzing data. Through this software the data can be analyzed in different dimensions. It can also be categorized and summarized depending on the varied relationships that have been identified.
Data mining is not entirely a new concept in terms of technology. There are so many companies that use computer software to filter through volumes of data in a bid to analyze the market conditions and trends.
How does data mining work?
Data mining software can analyze patterns and relationships in data that is large and based on open ended user questions. There is different analytical software that can be used to carry out data mining:
- Machine learning
- Statistical data
- Neural network
Data mining in general seeks to establish the following types of relationships:
- Clusters – where data is grouped in items that are in accordance specific relationships and consumer preferences.
- Classes – where data that has been stored can be located in predetermined groups and used to improve businesses or ventures. E.g. increasing traffic to the business site.
- Sequential patterns – where data is used to identify future trends and possible behavior patterns.
- Association – where data is used in identifying different relationships and associations.
Data mining is done using different levels of analysis depending on the data, purpose and preference of the user:
- Artificial neural networks – these are non-linear predictive models which resemble biological neural networks.
- Genetic algorithms – techniques that use genetic combination, mutation and natural selection processes that are based on natural evolution concepts.
- Data visualization – a technique used to identify the complex relationships in multidimensional data. The relationships are represented in a graphical way.
- Rule induction – entails deriving important “if-then” rules from data that has been based on the statistical significance of tests and results.
What is the importance of data mining?
Many companies today are embracing the concept of data mining. There are several uses of data mining which businesses can use. These include:
- Data mining can be used to determine the relationships between a company’s internal factors (e.g. pricing, packaging, staff attitudes and skills as well as advertisement) and external factors such as (economic indicators, market trends, consumer preference and competition). This can help to determine transactional data
- Data mining can also help retailers to determine the best records of sales and come up with relevant and focused targets of promotional sales.
- Data mining can also be used to select the best and most efficient suppliers for business products and thus help to boost profits.
- Data mining can also be used to detect the fraudulent deals and avoid them.
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