Six ways Data Mining helps businesses make better decisions

It’s widely regarded that data mining is one of the key ways of making better business decisions. But what are the actual classes of tasks and opportunities data mining provides to make use of bulk data? Let’s have a closer look.

Data Clustering

Cluster analysis (also known as clustering) is the task of grouping objects in groups that are more similar to one another than they are to others. It the main task of exploratory data analysis and a common technique for statistical data analysis.

Data clustering has applications in numerous fields, from biology to medicine, but it is also used to analyse social networks, for example, to recognise communities within a large number of people. Clustering is also used in search result grouping, where it helps create a relevant set of search results.

Disciplines from crime analysis to field robotics and finance all benefit from data clustering.

Statistical classification

Have you ever wondered how your inbox determines whether an incoming email is a spam or non-spam? It utilises statistical classification. Roughly put, statistical classification determines into which set of categories an observation belongs.

Individual observations are often analysed into a set of features, which may be either categorical (blood types), ordinal (small, medium or large), integer-valued (a number of occurrences of a particular word in an email message) or real-valued (for example, blood pressure measurements).

Algorithms that implement classifications are called classifiers. Classification has applications in computer vision, speech recognition, search engines, pattern recognition and many other fields.

Anomaly detection

When you have big batches of data, you tend to have anomalies. Anomaly detection in data mining is the identification of rare items, observations or events that differ significantly from the majority of the data.

These anomalies are called outliers and usually will translate into some kind of a problem. These problems range from errors in a text to medical issues or even bank fraud.

Some of the most common uses of anomaly detection are intrusion detection, fraud detection, system health monitoring etc.

Association rule learning

Also known as dependency modelling, association rule learning searches for relationships between variables. If you want to know how supermarkets find products to recommend to you, then they probably use dependency modelling to determine which products are frequently bought together. This data can be used in marketing to make decisions on product placement and promotions.

Regression analysis

Regression analysis is a statistical tool often used for predictions and forecasting. Regression analysis estimates the relationships between a dependent variable and one or more independent variables. It can be used to assess the strength of the relationship between variables to model the future relationship between them.

Regression analysis can be used to forecast financial statements for a company to determine how certain assumptions or drivers of the business will impact revenue or expenses. This kind of analysis might reveal, for example, a very high correlation between revenue and the number of stores operated.

Automatic summarisation

It’s virtually impossible to go through large sets of data one by one to get a bigger picture. But sometimes, a big picture with only the most relevant information is all you need to know what to do. This is where summarisation comes in handy. Summarisation creates a subset of data that represents the most important or relevant information within the original data set. It is almost like a book report that represents the most important narratives and key events to get an overview.

Summarisation can be used for everything from texts and documents to pictures and even videos and can be applied to match a specific query.

Do you have an idea how data mining can help you make better business decisions?

If this all sounded fascinating, then maybe it’s time to see how big data and data processing can help you make better business decisions? Then maybe it’s time to dig into some of your business data and see where your hidden advantages are. The numbers don’t lie – get in touch with us!