Table of contents
- What is data mining? Does the tool have a free version?
- Methods and effects of data mining tools
- Advantages of introducing paid data mining tools
- Should you choose a free or paid data mining tool?
- Points to consider when choosing a data mining tool
In the business environment, the value of data analysis has never been greater, and it is no exaggeration to say that those who control the data control the market. When analyzing huge amounts of data, you can simplify your work by using the power of data mining tools. This article provides an overview of data mining, recommended tools, and points to keep in mind when choosing a data mining tool.
What is data mining? Does the tool have a free version?
First, to understand the basics of data mining, let’s check the meaning and purpose of data mining.
What is data mining?
Data mining is a tool that analyzes large amounts of data using various analytical methods such as statistics, pattern recognition, and artificial intelligence to extract correlations, trends, and knowledge. By using data mining to analyze data that is normally accumulated but difficult to find value in, it is possible to unearth “valuable data and knowledge” and gain new knowledge from it. .
There are paid and free versions of data mining tools. The biggest advantage of the free version is that it does not incur any costs, but because the functions included are limited, it may not be possible to perform sufficient analysis depending on the business purpose. Therefore, when introducing one, compare the two and choose the free or paid one, taking into consideration whether it will achieve your company’s objectives.
Methods and effects of data mining tools
Data mining processes information using three analytical techniques: classification, prediction, and association in order to make it easier to handle huge amounts of data. Here, we will explain how data is actually analyzed, typical methods of data mining tools, and their effects.
Classify using cluster analysis
Cluster analysis is an analysis method that collects similar items from a mixed group of different items to create clusters and classify the objects. By using cluster analysis, it is possible to promote appropriate advertisements and suggestions to users whose behavior is similar to that of users who have purchased a certain product, contributing to the field of marketing.
Predict with logistic regression analysis
Logistic regression analysis is a statistical method that can explain and predict the probability that a certain event will occur based on various factors. It contributes to lean product management by accurately predicting sales trends and customer trends. It also helps guide how marketing techniques should be used.
Discover relationships with market basket analysis
Market basket analysis is an analysis method that identifies products that are likely to be purchased together by analyzing purchase data. It is effective for marketing strategies and sales improvement, such as product display, special sale items, campaign product selection, and product purchasing.
Advantages of introducing paid data mining tools
Paid versions of data mining tools have many benefits that free versions do not have. From here, we will explain the benefits of introducing paid data mining tools.
With paid data mining tools, if you run into trouble during installation or operation, you can receive support from a dedicated person in charge. Since you can ask questions, consult, and make requests directly, you can save time and money.
Paid tools are safer in terms of security. The data required for data analysis often contains important information such as personal information and confidential information. By choosing a paid tool with solid security measures in place, you can reduce the risk of information leakage.
Large sharing scope and data capacity
Some paid data mining tools have a function that extracts and aggregates frequently appearing keywords, and a function that allows you to read trends by arranging the results in chronological order and creating a graph. These functions expand the range of sharing of analysis results, including use in presentation materials. Another strength of the paid version is that it requires a large amount of data for data analysis.
Many free data mining tools are specialized for personal use and cannot be used by multiple people at the same time. Therefore, if you have multiple people in charge or a large number of people using the tool, we recommend considering the paid version.
Should you choose a free or paid data mining tool?
So, should you choose a free data mining tool or a paid one? Here, we will introduce the characteristics of each and the points to consider when selecting one.
Cases where free tools are recommended
If you want to deepen your understanding of the performance and functions of a data mining tool by experiencing it first, a free tool is sufficient. However, please note that depending on the analysis method you are looking for, it may not be available for free. Also, free tools lack official support. Therefore, learning costs and time costs are required for the knowledge and experience to analyze data.
Cases where paid tools are recommended
If you want to use it in earnest for your business, we recommend using paid tools. The major difference from free tools is that in addition to receiving support during installation and operation, it is also easier to utilize the analyzed data. It depends on the paid tool you use, but paid tools are overwhelmingly more functional when it comes to data sharing and interfaces for detailed data analysis.
If you are worried that the market research and research you are currently conducting in-house is not enough or that it is difficult to obtain results, we recommend using a paid data mining tool.
Points to consider when choosing a data mining tool
When choosing a data mining tool, it is essential to check the following items. In order to improve the accuracy of data analysis using data mining tools, let’s deepen our understanding of the points to keep in mind.
Choose the tool that’s right for you
When introducing a data mining tool, the first thing you should discuss within your company is the purpose of data analysis. Even if you incorporate data mining tools without clarifying the purpose, it will be difficult to obtain the expected effects. Therefore, consider using data mining tools after clarifying how you want to utilize the results of data analysis for your company.
Calculate cost effectiveness
It is also important to list the costs of each data mining tool and compare them to see if they fall within your budget. It is a good idea to calculate the total cost and cost-effectiveness while checking whether it is a one-time purchase type or a monthly billing system. Also, at this time, do not forget to consider not only the initial cost and monthly fee, but also the training cost for employees to be able to use the system.
Clarify analysis targets and methods
By clarifying the target of analysis in advance, you will be able to see the data you need. For example, if you are aiming to increase sales, you can analyze the data more effectively by preparing data such as the age group of purchasers, the time of day of purchase, and the reason for purchase from past sales data. You can do this. Additionally, as introduced above, there are several methods for analyzing data, so it is a good idea to clarify which method to use.
Choose tools that are easy to use
Each data mining tool has different operability, required knowledge, and skills. Therefore, make sure that your employees can use the tool without any problems.
By introducing data mining tools, you can efficiently discover hidden business issues. Big data has many hints for dramatically increasing sales and ways to increase customer satisfaction, so it’s worth taking advantage of it.