How data mining can solve the problem of Big Data

media update's Aisling McCarthy talks data mining, and how it can be used to make sense of Big Data.

Data mining is the process of going through large sets of data to extract information and establish patterns. It can be a useful way to deal with the vast amount of Big Data, which is ubiquitous nowadays. Big Data poses a problem for many companies, as it can be overwhelming to deal with so much information, and difficult to identify trends within mounds of data.

The data mining process begins with the gathering of data, which is vigorously analysed and the relevant information is extracted. Once the most pertinent information is extracted, it is used to identify trends and patterns within the data. This information can be used to project future developments.

Data mining is a useful way to deal with the vast amounts of Big Data, as important information can be extracted, and then used to project future developments. The analysis of this data can help to solve problems and to shape strategies for predicted future trends.

Basket analysis is a branch of data mining, which offers businesses a way to see which items consumers buy in conjunction. Through data mining, retailers are able to pick up patterns in consumers’ spending and identify which products customers have bought together. Once these trends are analysed, retailers are able to recommend related products to consumers, based on what items they usually buy together.

Sales forecasting is another branch of data mining, which looks at when consumers have bought products in the past, and tries to predict when they will buy it again. For example, ice cream sales are much higher in summer than in winter, so retailers know to increase stock for the summer months. This also allows retailers to work out their predicted sales numbers, which can assist with budgeting.

Other uses for data mining can include identifying the number of potential customers in your markets, as well as creating marketing databases, which send information about certain products to consumers who are more likely to buy them.

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