Data mining software identifies patterns in large data sets, helping companies turn information into actionable insights. The process involves raw data conversion, mining programming script, and interpretation, and requires a solid understanding of data concepts. The software uses regression analysis, fuzzy logic, and algorithms to identify models based on user specifications, but poorly defined specifications and low data quality can negatively impact results.
Data mining software is a tool used to identify patterns in large data sets. This area of computer software has expanded dramatically in recent years as companies look for ways to translate large volumes of information into actionable insights for decision making. The ability to clearly identify cause and effect, patterns in human behavior, trends and other metrics is critical to successful management of any business. The benefits of data mining software are clear to most users, but how to get the information you want and how exactly the process works is poorly understood by the general business community.
There are three aspects of data mining software that describe the process: raw data conversion, mining programming script, and interpretation. This process is also known as knowledge discovery in databases (KDD) and is used to describe all aspects of data mining, including data structure, data access methods, and system architecture. There are a wide variety of companies offering data mining software, and a solid understanding of the concepts that drive this product is essential to the successful and appropriate use of the technology.
The first requirement for using any data mining software is to convert the raw data into a target dataset. For example, raw data is the database of all sales processed over a large period of time. A target dataset contains only data that meets a specific criteria. This can include transactions processed within a specific time frame. Included in the dataset specification are the individual fields that are included. This may include the date of the transaction, payment method, store location, product description and number of items purchased.
Once the specifics of the data set is determined, the data is cleaned to remove excess information, noise or incomplete data files. This process typically requires the use of programming skills, data management techniques, and a general understanding of the primary data concepts at work. A data mart or data warehouse is the most common tool used to store tables of data in a way that is easily accessible by the data mining software program.
The actual data mining programming scripts can be customized, or programmers can use standard scripts included in the data mining software package. The vast majority of data mining software programs use regression analysis, fuzzy logic, and algorithms to identify specific models that meet user specifications. Interpreting the results requires human intervention, time, and skills in statistics, pattern recognition, and related math skills. It is important to remember that the program can only return options based on user-supplied specifications. Poorly defined specifications and low data quality will negatively impact the validity of the results.
Protect your devices with Threat Protection by NordVPN
