Data Mining

Data mining is the ability to query large data sets. This requires advanced skills and is a promising solution.

What is data mining and its types?

Data mining is looking for hidden, valid, and potentially useful patterns in huge data sets. Data mining is also called as Knowledge discovery, Knowledge extraction, data/pattern analysis, information harvesting, etc.

What is data mining used for?

Data mining is a process used by companies to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs.

How does data mining work?

Data mining, or knowledge discovery, is the computer-assisted process of digging through and analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions.

What’s the relationship between machine learning and data mining?

Any academic discipline usually has three kinds of work: theory, methods, and applications. Projects and researchers usually often span one or two of these types of work, though often there are revolutionary renaissance-man types of researchers who straddle all three effortlessly. In the space of data, there are usually two kinds of researchers. Read the full article for more details.

What are the components of data mining?

There are a number of components involved in the data mining process. These components constitute the architecture of a data mining system. The major components of any data mining system are data source, data warehouse server, data mining engine, pattern evaluation module, graphical user interface and knowledge base.