Since the past couple of decades, the recent advances in Information Technology and related applications have provided companies with the perfect tools to achieve business success by promoting a higher level of customer interaction and internal as well as external organizational capability and efficiency. The data analytics process has improved and increased the quality of Business Intelligence thanks to the introduction of text mining applications, which act as a filter to help companies reduce the overflow of excessive and unusable data that circulates internally as well as externally on the world wide web.
Text mining operates to collect relevant and goal-oriented business information that can determine changes in customer preference and allow companies to respond faster to meet new trends, measure itself against even other bigger competitors, and ultimately increase customer satisfaction and allegiance. Many software companies like Expertsystem are great resources of using data and text mining applications that can aid a company achieve optimum organizational efficiency and reliable BI.
How text mining help your BI
Text mining’s capacity to sift through, analyze and correct at a speedy rate any errors in grammatical syntax, sentence structure, terminology or misspellings by data entry operators, also helps to reduce language barriers, in the end promoting more effective communication with clients, customers, investors and external partners or other industrial entities. It gets thing done by a process of decipherment that involves identifying and separating relevant text, numeric or non-numeric codes, or single words that have more meaning for the business objectives of a company. Some of these processes involve word stemming and the use TF-IDF scores to avoid duplicates and recognize differences in terminology.
The monitoring of social media channels and consumer chat groups is another added value to gain insight into consumer trends, and to forecast market fluctuations in stock and prices. The filtered information is then funnelled to the appropriate department/s that can implement the needed decisions.
The process of text mining eliminates the risk of losing valuable information that may be lost during codification (particularly of mixed texts) even when analyzing ‘free-form’ text— such as e-mails, documents, and call centre logs which most companies argue are extremely valuable for effective interaction with customers and clients.
Solving codification problems
Codification raises many problems for the simple fact that the majority of companies refuse to change their data analysis operational system, mainly because they have already invested significant amount of money and manpower to implement it and teach employees how to use it. They also argue that data validation at point of entry would slow down operational efficiency, doing more damage than poor data quality.
That is where text mining comes in; you do not need to change the IT infrastructure of the company to employ the applications, which come in single modules that can easily be applied as add-ons, and no employee retraining is necessary.
Cutting costs and resource consumption
A further significant advantage is that text mining reduces working time, thus cutting the cost for manpower and resources, and improving the overall company budget. It can create a data framework system that encourages participation from all levels in the organization.
At the same time, there are fears that the implementation of text mining will lead to down-sizing of the workforce, since it reduces manpower and work effort. On the other hand, it must also be recognized that because it leads to business growth and profit maximization, and in the process to closer joint-effort with the collaboration of all company levels, there would be greater opportunities for the company to extend its sphere of activity and influence, thus promoting the growth of its workforce.
Takeaway
With the humongous amount of data to analyze, BI requires businesses to adopt techniques that can speed up analysis while maximizing resource utilization. Text mining exists to solve those problems. Businesses need to consider to adopt text mining in their BI endeavors to get them ahead of the competition.
