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Overview
In this era where there is a lot of information to be handled at ago and actually with little available time, it is necessarily useful and wise to analyze data from different viewpoints and summarize it in such a way that it will take less time to interpret by the final user of that particular information.
This, in effect, reduces costs associated with processing data and information for the purpose intended and at the same time increasing the revenue base for the business through internal saving tactics. Data mining is the process by which data from different perspectives is analyzed and summarized into useful information. This task ensures that data achieve relevance in performing the intended duty. Data mining is also referred to as knowledge discovery.
During this period of high operation capacity of businesses, the role played by data mining cannot be assumed. Using statistical and mathematical techniques to dig through data warehouses helps in the recognition of significant facts, relationships, trend patterns, exceptions, and anomalies that might not be noticed by the concerned in the business environment. With this kind of approach, predicting customers’ behavior becomes very easy.
Areas of application for this software are also not few. First of all, it aids in market segmentation and direct marketing where the businessman knows the best way to get the highest response rate from the clients. This can be done by establishing the customer preferences. Data mining can also help a business entity to establish the level of customer runaways, that is, the number of potential customers who run away and join the competitor.
Fraud detection is made easy by this software, in addition to the fact that it creates room for interactive marketing. It is very easier to know the products common y purchased together by carrying out a market basket analysis. This will help the business in developing the products that can be purchased together and therefore gain from complementary effects of each other. Using the same software, trend analysis can be carried out, which will help in knowing the customer preferences and, therefore, the best service provision style best suited for the particular customers in question.
Discussion
Data mining is not just a hanging phenomenon, but it is part of the many series of analytical techniques, and it involves extracting, transforming, and loading transaction data into the depot data system. Secondly, there is storing and managing the data in a database system, after which provision is made for the data to be made available to analysts and technology experts. These experts analyze the data using application software to make sure that the data presented performs its intended duty satisfactorily.
Lastly, the data is availed in a useful design such as a graph (viewbi: group). This advancement has led to the rise of new developments like internet sales, web marketing, among other several recent developments like web seminars and web advertising. These developments have really led to more work being handled by a particular business entity at the same time ensuring the efficiency of the whole system.
Other types of analytical developments include business intelligence, data modeling, data visualization, metrics, and web analytics. All these are part of an information management system meant to improve the performance of the business and give, in the long run, a powerful result. This ensures a rapid return on the investment channeled into the business operations. Taking a look at the demo on the ACME bank’s profitability, it would be very easy to note that the whole operation of the bank is actually summarized in one place, making it very easy to understand the operations as a whole with just a glance at the demo (Bank profitability. SWF). This enhances cost minimization since all the costs that would be involved in the whole issue if it were to be checked stage by stage and department by department.
The quarterly internet sales on the viewbi (ViewBI: Group) is a good summary giving the general presentation of the scorecard detailing the finance of the group in terms of finance and revenue by category. Development and use of these financial visual models, offers a vibrant amalgamation of “supposing” scenarios and drill-down features which are helpful in future projection, financial performance, growth, risk, and market share. Every specific value point shows the viewer the underlying individual report which ca be used to modify sales growth rate and all other germane accounts measured.
In conclusion, the springing up of the analytical tools for analyzing data has improved the rate at which the operations are carried out and made it possible for data to be scrutinized from different perspectives, categorized and summarized in a concise manner.
Reference
ViewBI- Business Intelligence Reporting Dashboard. ADWEB Agency. 2007. Web.
Crystal Xcelsius Templates. Business Objects SA. 2007. Web.
Palace B. (1996) Data Mining: What is Data Mining? Web.
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