Data Mining is a technique of sorting through long data sets to identify patterns and relationships which will solve business problems through data analysis. Data mining techniques and tools enable enterprises to express the trends and also make important business decisions. It is considered to be a part of data analytics and also uses advanced techniques to find useful information in data sets. Data mining is a step in the discovery of knowledge discovery in the database process, it is a data science technology for collecting, processing, and analyzing data. Data mining and are sometimes will be referred to interchangeably.
Why is Data Mining important?
Data Mining is a component of successful analytics initiatives in organizations. The information it generates will be used in business intelligence and advanced analytics applications that involve the analysis of historical data. Effective data mining has many aspects of planning business strategies and mining operations. This includes customer-facing functions such as marketing, advertising, sales and customer support and manufacturing, supply chain management, and finance. Data Mining assists in fraud detection, and risk management. It also plays an important role in health care, government, sports, and so on.
How does the data mining process work?
Data mining is done by data scientists and other skilled BI and analytics professionals, It can also be done by data-savvy business analysts and others. It is a core element that includes machine learning and statistical analysis, along with this data management tasks will be done to create data for analysis. The data mining stages are:
- Data gathering- The data for analytics applications are identified and assembled. The data can be located in different source systems like a data warehouse or a data lake, an increasing repository in big environments which contains a mix of structured and unstructured data. Here the external data sources can be used. Data comes from a data scientist that often moves it to a data lake for the remaining steps in the process.
- Data preparation- This stage includes a set of steps to get data ready for mining. It always starts with data exploration, profiling, and pre-processing which is followed by data cleansing work to fix errors and other data quality issues. Data transformation will also be done to make data sets consistent unless a data scientist is looking to analyze unfiltered raw data for a particular application.
- Mining the data- When the data is prepared, a data scientist chooses the appropriate data mining technique and then implements more algorithms to do the mining.
- Data analysis and interpretation- The data mining results will be used to create analytical models which can help drive decision-making and also other business actions
Data mining software and tools
The data mining tools are available from a large number of vendors, as a part of software platforms that also include other types of data science and also advanced analytics tools. The important key features are provided by data mining software that include data preparation capabilities, built-in algorithms, and also tools that are deploying models, and also scoring how they perform. Many different open source technologies can also mine data, including dataMelt, Elki, and Orange. Some vendors provide open source options.
Benefits of data mining:
There are many business benefits of data mining which come from the increased ability to uncover hidden patterns and trends in data sets. Many data mining benefits have been listed below:
- More effective marketing sales- Data mining will help the marketers to understand better customers’ behavior and preferences. Sales teams can use data mining results to progress the lead conversion rates and sell the products and also services to the customers.
- Better customer service- By data mining, companies will identify potential customer service issues more promptly and give contact center agents up-to-date information to use calls and online chats with customers.
Questions
- What is Data Mining?
- What are the advantages of Data Mining?
