What is data mining and how does it work?
Data mining. The term “data mining” is in fact a misnomer, because the goal is the extraction of patterns and knowledge from large amounts of data, not the extraction ( mining) of data itself. It also is a buzzword and is frequently applied to any form of large-scale data or information processing ( collection, extraction, warehousing,…
What are the requirements for data mining algorithms?
Before data mining algorithms can be used, a target data set must be assembled. As data mining can only uncover patterns actually present in the data, the target data set must be large enough to contain these patterns while remaining concise enough to be mined within an acceptable time limit.
What is data warehousing and mining software?
Data Warehousing and Mining Software. Data mining programs analyze relationships and patterns in data based on what users request. For example, a company can use data mining software to create classes of information. To illustrate, imagine a restaurant wants to use data mining to determine when it should offer certain specials.
What is the best format for data mining models?
For exchanging the extracted models – in particular for use in predictive analytics – the key standard is the Predictive Model Markup Language (PMML), which is an XML-based language developed by the Data Mining Group (DMG) and supported as exchange format by many data mining applications.
What are the risks of data mining?
Data mining can be a cause for concern when a company uses only selected information, which is not representative of the overall sample group, to prove a certain hypothesis. Data mining is the process of analyzing a large batch of information to discern trends and patterns.
Should you look at data mining as a separate entity?
In the end, you should not look at data mining as a separate, standalone entity because pre-processing (data preparation, data exploration) and post-processing (model validation, scoring, model performance monitoring) are equally essential.