In most cases, those who hear the term data mining think about miners digging and looking for gold and diamonds.
Well, they are not far away from the truth. Data mining is focused on digging and gathering information chunks that are found in data. Of course, instead of shovels and other similar tools, data miners rely on BI (business intelligence) solutions.
Data mining 101
Modern businesses are complex and rely on data. This means that the amount of data has increased. This is how the phrase big data emerged. Big data is the massive amount of data that businesses and organisations have to check and analyse when they want to find useful information.
For instance, every big retailer usually has different promo sales, inventory, POS systems and other elements that make their business successful. Every individual system that we have mentioned comes with helpful data that is mineable and based on this data, business owners, and organisation leaders can make sound decisions. So, the value of data mining can be compared to diamond prices – they are always going up.
When talking about selling diamonds and other items, it’s good to know that data mining can actually improve retail different services. Namely, it is a well-known fact that retail businesses are relying on web scraping.
This specific industry has to handle tons of data and information that come from sales, customer shopping behaviour and history, input, supply, demand and other important retail indicators and services. In addition, the pricing of any item is extremely important.
Data mining is taking care of many of these activities – monitoring customer behaviour, market changes and trends, setting up the best prices for different items, categorisation of different products depending on customer behaviour
and many other things.
Of course, data mining affects other industries too including telecom industry, biomedical research, educational organisations etc.
How does it work?
With the help of data warehouses, information is extracted from a wide range of systems, converted into an ordinary format and uploaded into the data warehouse. Extract, transform and load or ETL is the name given to this sophisticated process. When the obtained info is merged and converted, experts can work with the data.
In the past, the consolidation of information was conducted within a specific time frame like – once a day, once a week, bi-weekly or monthly. One of the main reasons why intervals were used was the fact that databases had to be offline while the data was processed. As you are probably aware, the business that is open 24 hours a day, 7 days a week can’t be down simply because data must be updated.
As a result of that, many businesses and organisations had old, obsolete and/or irrelevant data. Even with irregularly updated data, organisations in the 1990s were operating fine, but today it’s impossible to run a business in this way.
Nowadays, organisations are using real-time extract, transform and load process. In this way, users can warehouse data smoothly and without interruptions. The vast majority of BI solutions are able to provide continuous ETL data processing, but this doesn’t mean that the process ends here.
When the mining is finished, users are looking at the reports of summarised data mining process. Two decades ago, these reports needed special knowledge and expertise to be created and maintained.
Today, thanks to modern technology the reports can be adjusted and limited and it doesn’t take much time to figure out how to set them up and use them. In other words, this process is taken down to the ordinary user level. Making a custom report is easy and requires drag and drop activity. Hopefully, this article will help you how data mining works and why is it important.