If you deal with data then you must have heard of the term data mining. It refers to the process of finding correlations, patterns, and anomalies within data sets so that one can make correct predictions.

This is very important because businesses rely on data to make reliable decisions. In this article, we’ll talk about data mining and its important in the world of business.

Let’s get started:

What Is Data Mining?

The term data mining was introduced in the ’90s but we have been using and processing data much before that. It is based on three scientific disciplines namely stats, machine learning, and artificial intelligence.

Data mining is a fast-evolving technology especially due to the huge potential that big data offers. We have more data than ever to process and understand. We have moved from manual, time-consuming, and tedious practices to automated, easy, and quick data analysis. The more complex a data set, the more information you can get through data mining.

The data mining process is quite straightforward. It involves six steps:

  • Gathering
  • Exploration
  • Preparation
  • Modelling
  • Evaluation
  • Deployment

Who Uses Data Mining?

Data mining is generally used by businesses. These include a variety of industries such as:

  • Communications and Multimedia

Competition is stiff in this industry as the potential is huge. New telecommunication companies are coming up at a rapid pace. Since they hardly differ in terms of price, their USP ends up being how they cater to customers. For this, they need data that can help them gauge what a customer needs so they can provide ‘em exactly that.

Companies need to know what kind of communication related services customers want. For example, do they want cheaper voice calls or more internet bundles? Information like this can help them customize packages that clients want, which can be the difference maker at the end of the day.

  • Banking

Banks earn money by issuing loans. They have to keep a record of everything from how much money is in circulation to previous client data, which they often use to decide if they should or shouldn’t issue a loan. Other than this, banks and other financial organizations also invest money in different assets to earn a profit that they often share with clients.

They typically use automated algorithms to understand clients and keep a tab on transactions. Since there are thousands of daily transactions involving billions of dollars, banks cannot afford to include incorrect data. A single missing or incorrect number can lead to major problems.

This is why the banking sector is willing to spend millions to ensure data remains correct and safe.

They use this data not only to understand clients but also to understand market so they are well aware of market risks and upcoming situations including political changes. Plus, data is also important from a compliance perspective.

  • Education

The education sector includes all educational institutions and government organizations that work to spread education. They have to keep a record of student progress that they use to predict performance.

This data helps institutions understand what kind of students they have and what changes they need to bring to the curriculum to improve the delivery of materials.

Moreover, this information also helps educational institutions differentiate between bright students and students who need special attention. This is very important since no two students are the same.

Thanks to data, schools do not have to make report cards and other such documents manually. Computers can handle computation and make a list in the desired order, such as top students.

  • Insurance

Insurance companies use data to solve issues related to customers. They also use data mining to price products based on market demand and competition.

Insurance companies need a lot of generic data, too, including stats on the number of road accidents and amounts paid to clients over the years. They use this information to find new customers and show the importance of insurance to prospective clients. Plus, data helps them identify and solve fraud cases.

  • Manufacturing

Manufacturing can be difficult, especially if you do not know how much you have to produce. Data mining allows companies to have a clear picture regarding demand and supply so that they do not end up over or under producing as both these situations can be harmful.

  • Retail

Sellers keep a large database of customer data including addresses and payment details. They need this information not only to ensure the correct delivery of goods but also to improve relationships and offer excellent customer service.

They use data to understand what customers want. For example, are they interested in lower prices or special 2-for-1 offers? A lot of online and offline stores offer special discounted rates. They use data to understand their clients and offer them exactly what they want.  Plus, they also use data mining to gauge customer reactions and come up with marketing plans.

The retail industry will struggle a lot without access to data that helps it take such decisions.

In addition to this, they use data to detect problems related to quality. Other than this, data helps businesses calculate expected maintenance time and schedule so that production can continue at the required speed.

  • Research

It does not matter what kind of research someone is performing, they will need data – a lot of it – in order to conclude. Individuals and institutions both work on research papers for a variety of purposes.

They need data in order to reach a true conclusion but issues with this data can lead to the verdict being rejected or incorrect. This is why they need data mining so they can have a better understanding of the data that they have collected.

Research may appear like a simple job but it can take some companies and individuals years to compile data and run tests on it to reach a conclusion. It is only due to research that today we know how much people spend and on what they spend. Information like this helps businesses come up with the right strategy.

Why Does Data Mining Matter?

data scienceIf you are still unclear about the advantages of data mining then check out these points:

  • Less Wastage: Data mining helps save resources. We have highlighted above how it allows companies to know exactly how much of an item is needed. As a result, there is less  wastage, which helps not just the company but the economy as well since wastage of scarce resources can be bad for everyone involved.
  • Time Saving: Data mining saves time as it allows businesses to manage data automatically, removing the need to do manual tasks. As a result, we can  get more in less time. Plus, there are fewer chances of risks and errors as the output is more reliable.
  • More Return on Investment: Data mining allows marketing companies to build data models and make predictions. They also use data to create marketing campaigns that offer good returns. As a result, companies enjoy higher profits. Moreover, this applies to every industry. Real estate firms, for example, use data to predict  price fluctuations. The same goes for the stock market where investors use different metrics to predict the future rate.

All in all, data mining makes us ask the right questions which helps us understand our data and get more out of it.

Data Mining: Conclusion

When it comes to data mining, the most important factor is the quality of data. It should be correct and poor quality data may result in issues such as late processing or biasness.

Consider using tools like WinPure Clean & Match to clean and dedupe your data and make it usable. We offer a free trial, so sign up today and see how our software can help you save money and make better decisions.

Written by Moe Sid

Moe Sid is the Content Editor at WinPure, and for the greatest part of his life he's been working as a content writer and ESL teacher. He enjoys writing web content and copywriting as well as blogging on the data management topics.

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