Unlike data analytics, which focuses on finding specific solutions to business-related questions, data mining involves finding answers to questions you may not have realized you could have. It involves looking for patterns that may be otherwise overlooked because you weren’t aware they existed.
Data mining requires a skilled professional who understands how to look through the noise to find useful sound bites that can direct future efforts. And that process can be daunting.
However, as data scientists become more adept at sifting through Big Data caches, the potential of the specialty grows. And that means the future of data mining is full of potential. The use is simply dictated by the industry in which you operate and the types of data available.
Retail Products and Services
One of the strongest applications of data mining falls in the retail products and services sales sector. Often, retailers have mechanisms in place to collect data regarding individual or family shopping habits, including what was purchased and when. Within these data points lay patterns regarding what leads a shopper to purchase the way they do.
Whether it is anticipating major life changes in the works or finding product correlations that may not be initially obvious to an outside observer, understanding customer behavior provides significant opportunities to improve marketing efforts. Additionally, it allows retailers to make specific cross-selling recommendations or improve product placement within stores to increase sales numbers based on previously unidentified relationships.
Within manufacturing, production and warehousing facilities, data mining can be used to improve processes without having a specific target in mind. Finding bottlenecks in the system can help determine future equipment or hiring needs, as well as serve as a starting point for research regarding process improvement.
Often, businesses operating in these sectors see increased profits when the processes are optimized. This includes the proper allocation of resources as well as investment in the right equipment-oriented areas. By understanding which portions of the process represent the weak link in the chain, more targeted analytics can help root out potential causes and lead to new solutions.
Location data is collected in droves through a range of mechanisms including social media and smartphone applications, and this data has the potential for almost any business type.
Location-oriented data mining also has significant potential in regards to retail sales. The ability to view how your customers move through a space, ranging from entire cities to small shopping centers, can also improve marketing efforts. Understanding where your customers are, where they go and how long they are there increases insight into their overall behavior.
However, coming up with targeted data analytic algorithms to find these answers without some understanding of the initial data is often too cumbersome to manage. Data mining allows an initial picture to be created and increases the likelihood of relevant outputs when algorithms are based on this starting information instead of taking shots in the dark.
For companies focused on transportation, being able to monitor deliveries in progress can help create better shipping routes for faster delivery timetables. Being able to get products to their destinations more efficiently can lead to significant financial benefits as well as improved customer satisfaction, all of which have the potential to increase profits.
Data Mining Expertise is Needed
As with many data discovery-oriented work, having a skilled data scientist available to create and support methods for performing data mining analysis is critical. Regardless of the quality of the information, it will only produce results based on the skill level of those performing the work.
Are you looking for a data mining specialist?
If you are looking for a data mining specialist, Solving IT can help you find your ideal candidate. Contact us today and see how adding a top data scientist to your team can improve your data mining operations.