Data mining as a concept is gaining popularity, but not many know what it stands for. Many online companies talk about how they use data mining to improve the quality of their services.
But what is data mining? Is it even legal?
What Is Data Mining and How Does It Work?
Data mining is a process used by companies and data scientists to extract information and find trends in raw data. The data used in mining can come from multiple sources such as online surveys, data collected through cookies, or public records.
But not all data sets are equally beneficial. The data needs to be accurate and without bias, consistent with as few gaps as possible, and large in volume to get authentic results.
Because you work with raw data instead of pre-made statistics, data mining can be a versatile tool. You can process the same data set multiple times in different ways, looking for various trends. That makes the insights from a single data set virtually unlimited.
There’s no clear-cut data mining technique, as extracting underlying trends requires a lot of creativity and skill. But the process can be broken down into five main steps.
1. Sourcing the Data
The first step is to find a source for your data and import it onto a storage server. This is where first impressions and data sources matter the most. You need your data source to be credible to ensure your results are trustworthy.
2. Picking the Work Environment
Whether you’ll be working locally on your device or using a cloud-based environment, now is the time to transfer it. Your environment of choice needs to be powerful enough to handle the amount of data you’re going to process. If you’re working with a team, accessibility is a priority, making cloud-based environments the best option.
3. Data Segmentation and Categorization
Whether the data you’re working on comes tagged or not, you need to organize it into categories related to the type of information or patterns you’re aiming to extract before you start processing it. Depending on the data's size, you might need to work on it in sections instead of as a whole.
4. Data Mining
After preparing the data and determining what you want to do with it, comes the actual process of mining and extracting information. You can use specialized software for this step or work independently using a compatible programming language such as R, Python, or SQL.
Data mining uses mathematical models to find and extract base-level insights for raw data. Although, you shouldn’t confuse it with data analysis, which uses the data and insights, often produced by data mining, to construct models and predictions.
5. Translating the Results
On their own, the mining results can be hard to understand. The final step is to visualize the data by translating it into graphs or tables. While the visualized results aren’t of much use for future analysis and mining work, they make it easier to understand and share your findings.
What Is Data Mining Used For?
You can use data mining to find out information about anything that you have raw data on. However, large businesses and online websites often use it that mine their data looking for predictions and behavioral analysis.
Companies that work in retail or e-commerce collect data from user’s accounts by conducting surveys or logging customer and user activity on their website or app. They can then mine the data looking for trends in purchases, from time of day and week to the frequency of visits and correlated spending.
In fact, data mining is what allows stores to send people notifications and discount coupons at times they’re more likely to buy. Not only would this result in higher revenue, but also more effective and cost-efficient marketing.
But it’s not just businesses that use data mining. You can find the direct influence of data mining in crime analytics, allowing governments to determine which areas and times of day have higher crime rates.
Data mining also plays a role in weather forecasting. It helps meteorologists analyze massive volumes of weather data collected about the climate as a whole or a specific location over a period of time.
Is Data Mining Illegal?
In of itself, data mining is not illegal. The problem arises with the source of the data and what miners do with the results.
The data needs to either be public knowledge, such as weather data, or obtained consensually. That means users of websites and apps and participants in online and physical surveys need to be made aware that the company will keep their answers and information for analytics and mining.
Companies and institutions that don’t have permission to use data could be breaking privacy laws, both locally and off-shore, depending on the data source. Not to mention, most countries ban the use of data mining insights to discriminate against individuals based on age, sex, gender, race, or religion.
How to Get Started With Data Mining?
Now that you know what data mining is and its legality, you might be interested in trying it out yourself.
Data mining isn’t restricted to large corporations with tons of resources and computational power. As long as you have a field of study you’re interested in learning about and legal access to data sets, you can start mining for info.
The first step is getting data ethically. Luckily, you don’t have to buy it or create an online survey. There are several public data sets on a variety of topics that you can analyze for free you can find on:
As for software, you can choose from a variety of free data mining tools. For one, there’s Orange, which is a Python data mining software suitable for beginners. But if you’re looking for software to run advanced mining algorithms, you can use the open-source data mining tool, R.
If you’re interested in mining but not sure you have what it takes, you can start by learning the basics of data analysis and manipulation.
The Future of Data Mining
With the age of data and information still in its early stages, data mining will only grow in popularity. While ethical concerns might still be an issue, in the right hands, data mining can be a force for good and knowledge instead of evil and mischief.