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CSE2DBX Database Fundamental Assignment Help
Data mining is a type of process which is used by different organizations for the conversion of any kind of raw data into information which can be utilized by the organization. This report focuses on the process of data mining and the advantages offered by it. Data mining can be done with the help of a number of applications or software. These applications can be helpful in finding a specific type of pattern in the data and use that pattern to develop different types of methodologies and strategies for the betterment of the business. The report also focuses on the use of this technology in different fields. The process of data mining depends on a number of factors including a collection of the raw data from different types of resources. It also depends upon the data ware housing of the collected data so that it can be utilized in the organization.
Description of data mining
Data mining is a type of methodology or process which can be helpful for the collection of a large amount of data. After collecting the data, it is sorted out so that useful information can be obtained from it. Thus data mining can be helpful in finding different types of relations and patterns which exist between data. By analyzing the data, information which can be used by an organization for its improvement can be obtained. The useful information which is obtained with the help of data mining can be helpful in making better decisions related to the business of the organization. The process of data mining takes place in a number of steps. These steps can be described below:
1. Collecting data from different types of sources
2. Loading the data into warehouses
3. Storing and managing the data which is present in the warehouses with the help of cloud or servers
4. After that, the data collected in the warehouses are analyzed by a number of people including analysts and IT experts. These people can help in organizing the data.
5. In this step, the analyzed data is examined with the help of a number of applications. After the examination, the data can be organized into different tables so that it can be utilized by the organization.
These are some of the steps which take place during the process of data mining.
The data collected in the process of data mining can be related to the customers of the organization. It can help the organization to fulfill the requirements of their customers and develop products with more usability. The more understanding an organization have about their customer’s needs, more products with better functionality can be developed which can be helpful for the customers. There are a number of parameters related to the process of data mining. One of the parameters is the association rules. These rules are created by performing analysis of the data (Rouse, 2017).
Another one of the data mining parameters is the path analysis. Path analysis is also called as sequence analysis and it can be used for finding different types of patterns which are present in the data. Classification parameter is another one of the parameters related to data mining. This parameter can be used for finding new patterns which are present in the data. It can be helpful in finding new ways for organizing data in the organization.
Importance of data mining
Data mining is important for an organization in many ways. Data mining can be used by an organization to find useful information from a pile of data which is collected from different types of sources. This can help the organization to make better decisions and lead the organization to make improvements in its business. Data mining can be helpful in finding the data or information which is relevant for the organization. It helps the organization to save time as only useful data is used for the development of a product or services. Data mining is also important because it allows organizations to speed up their decision-making process.
Data mining allows the people of an organization to find any kind of patterns which are present in the data collected from various types of sources and use those patterns and relationships to make prediction related to the betterment of the business.
Data mining has its importance in different departments of an organization. Marketing or sales department of an organization can use the process of data mining to collect and analyze the data of millions of customers. The information received from this data can be used develop better marketing campaigns for the organization.
Different industries related to finance sector can use data mining to develop risk models. These models are helpful in finding different types of risks which are associated with the business (Sas, n.d.).
Data mining implementation and software
Implementation of data mining process can be done in a number of steps. These steps can be described below:
1. First of all, a large amount of data is collected from various sources. This data could be related to sales, marketing or finance department of the organization.
2. After collecting the data, data is analyzed by a number of experts in the organization. The analysis is done with the help of a number of applications or software and it can help in finding useful information which can be beneficial for the organization.
3. With the help of this information, a model is created which can be used for the development of the product. This model undergoes the process of evaluation to find its efficiency.
4. These models are deployed in the organization and a number of decisions can be made on the basis of these models.
These are the stages involved in the implementation of data mining process. The different stages included in data mining can be shown with the help of the following diagram:
There are a number of applications or software which can be used for performing the process of data mining. Some of these applications are paid while some of these are free. Some of these applications which are open source can be given below:
RapidMiner: It is a kind of tool which uses Java language and can allow an organization to carry out different types of analytics. The analytics are offered with the help of frameworks which are based on templates. RapidMiner also allows the users to perform visualization of the data collected from various sources. It can also be used for performing statistical modeling and predictive analysis.
WEKA: WEKA is another one of the applications which are helpful in performing data mining. This software can be used in the algorithms which are utilized in different types of the analysis process. This software is open source and it can be used by anyone with access to the internet.
R-language: This language is widely used in many organizations for performing data mining. With the help of this software, data analysis can be performed with ease. This software is popular because it can be used without any kind of difficulty and training (Goopta, 2014).
These are some of the applications and software which can be used for data mining. These tools can help an organization in making better decisions.
Data mining in industry
Data mining is used in different organizations and industries with the help of a number of methods and processes. When data mining is used in an industry then, first of all, different sources which can be used for collection of data are identified. After identification, data is collected from these sources and a number of data points are selected. These data points undergo the process of analysis. This analysis helps in finding useful information which can be used in the industry. On the basis of this data, different models are created. These models can be utilized to make better decisions for the organization which can improve the business of that organization or industry. This data mining is used in an industry.
Data mining is used in different types of industries. Some of these industries are given below:
These industries utilize the process of data mining to find important data for their organization which can lead the organization to better decision making (Brown, 2014).
This report was started with the purpose explaining the process of data and mining and its application in different types of industries. The report successfully explains data mining and use of it in different types of fields. I have included a number of technologies in this report which can be used for the collection of data from different types of sources and analyze that data to find information which is of use. This report can be helpful for learners as they can learn about the importance and use of data mining in different fields. Learners can also learn about the implementation of data mining in different types of fields. Data mining can be helpful for an organization in making better decisions for an organization.
Brown, M., 2014. 5 Steps to Start Data Mining. [online] Scitechconnect. Available at: http://scitechconnect.elsevier.com/5-steps-start-data-mining/ [Accessed 7 Sep. 2017].
Goopta, C., 2014. Six of the Best Open Source Data Mining Tools. [online] The New Stack. Available at: https://thenewstack.io/six-of-the-best-open-source-data-mining-tools/ [Accessed 7 Sep. 2017].
Rouse, M., 2017. Data mining. [online] TechTarget. Available at: http://searchsqlserver.techtarget.com/definition/data-mining [Accessed 7 Sep. 2017].
Sas., n.d. Data Mining: What it is and why it matters. [online] Sas. Available at: https://www.sas.com/en_au/insights/analytics/data-mining.html [Accessed 7 Sep. 2017].