Importance of Data Mining in Big Data

Data Mining

Data Mining in Big Data is important due to the massive impact it has on businesses. Companies are leveraging their data to achieve a number of business goals, such as better customer service, efficient operations, and even better outcomes for products or services. But how does data mining help these companies? And how should data mining benefit you? We’ll discuss some of the main ways how data mining can benefit businesses.

  • How is Data Mining helpful? 
  • Benefits of Data Mining 
  • Tracking & Segmentation of Sales 
  • Incentives 
  • Accurate & Useful Insights 
  • Success of Data Mining

Tracking & Segmentation of Sales 

As customers shop, they usually don’t want to be sold to again. They may have several transactions with the same merchant and haven’t bought anything else from them in the past. This makes sales tracking and segmentation very important to businesses. By gathering this information from customers, they can target their marketing efforts to those customers who show the most interest. For example, if a customer buys a particular product eight times in a year, then the business could segment that customer based on the number of times they buy the product, the frequency of purchase, what kind of purchase they made (such as a shampoo or a pair of jeans), and whether the purchase was impulse or a planned purchase. Segmenting customers like this allows businesses to build a profile of their target market which, in turn, gives them an easier time making recommendations to their target customers.


Incentives can also be a powerful motivator for customers. Incentives can be anything from a discount to free shipping to a trial period. By using incentives, business owners can take advantage of customer behavior to gain a foothold in their target markets. They can also use incentives as a way to make purchases from customers that may not be in their interest at first. For instance, giving a discount to customers who bring a large order to the store for the day after a particular holiday can increase sales and increase profits.

Accurate & Useful Insights

Big Data visualization tools can also help a business generate accurate and useful insights. A visual representation of the data can be used to visualize relationships among variables. This helps show the impact of one variable altering another and gives a business a glimpse into the true relationship between all of the variables. It can also show the effect of changing parameters on the outcome. Visualization tools can be complex or simple.

Once data mining techniques are in place, it is important to extract meaningful information. Customers tend to be reluctant about sharing personal information online. However, businesses can employ techniques such as elicitation, elimination, segmentation and/or averaging to extract the appropriate information.

Success of Data Mining

There are many companies that have made use of data mining successfully to improve their processes and bring greater profitability. However, some businesses choose to take the process lightly, resulting in lost time and wasted resources. When data mining is performed carelessly, it can also produce unintended consequences. Big data mining should be a careful balance between revenue generation and sensible business practices.

The biggest payoff to data mining comes from the ease with which it streamlines processes. The faster a business can process information, the sooner it can reach the end users. It is also much more cost-efficient when it comes to data mining. Big businesses now need to compete for every piece of data available. If they fail to capture and process every bit of it, they will be at a serious disadvantage.


Businesses must ensure that the process of data mining is only done with consent and under the watchful eyes of senior managers. There are serious consequences for sharing data that does not serve the company’s interests. In addition, companies must be careful to avoid the risk of data mining becoming a black art. Hiding information from customers or intentionally under-charging is theft, not providing value or service.

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