Data Mining and Statistical Analysis 

Data mining:

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Today, data mining has become an increasingly important research area with the abundance of raw and unprocessed data available.

 

Because with the developing technology, the existence of unnecessary information along with the necessary information increases and it becomes difficult to reach the correct information in a short time. 

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That's why data mining is of great importance in order to reach the correct information in a short time.

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Therefore, in recent years, data mining has been frequently used by businesses that are conscious, believe in data mathematics and the power of data analysis, and have data analytics, mathematical and statistical interpretation capabilities and dynamics, rather than having only production and sales skills, regardless of their size. is used.

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If you ask why, because with the help of information technologies, businesses now have very serious data in their hands, both on the production and sales side.

 

However, this data is complex, unstructured and in large-scale accounting, finance or ERP systems, if any.

 

This data needs to be withdrawn from the systems and structured and turned into meaningful and interpretable reports.

 

However, unless the results obtained are reported to the senior management of the enterprises in a meaningful way and subsequently analyzed and criticized, unfortunately, these data do not go beyond the declarations, which are the basis of only mandatory legal notifications.

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Especially at the current level of our civilization, the above-mentioned data is gradually being collected both easier and faster, while at the same time it has a more complex and gigantic structure.

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For example, in a medium-sized company where I worked before,

If you were to receive a detailed sales report of the last year, a comprehensive production report or a broad-spectrum stock report in excel format, you will see huge data sets consisting of at least 2 million rows and at least 20 column headings according to the selection criteria.

 

However, these datasets will not make any sense unless you make them meaningful and interpretable.

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However, if those data sets were analyzed much more deeply and transformed into extraordinary reports and graphics that can be interpreted with multidimensional ease and presented to the top management of the enterprise, if the top management of the enterprise would criticize these reports and see the production, stock, sales and customer performance of the company in depth and review their strategies accordingly. Be sure, they can make decisions that lead to much more effective, efficient and profitable results.

 

Just like "this is our total turnover, we have sold to this many customers, we have exported the most to this country, we have sold so many products in total, this is the financial outlook for the next two weeks, this is the last stocks we have", which is extremely standard, simple, does not contain depth and hides the real performance. Senior managements, fed with reports prepared in the light of banal and vulgar data, only take decisions instead of decisions. 

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Although these decisions seem to revive the company in the short term, they may cause problems that are much more difficult to manage for the next generations of the family company in the medium and long term, and they will probably lead to problems.

 

Therefore, many companies in the world collect this big data; They know that they need to analyze and make meaningful in a versatile and extraordinary way to increase efficiency, to use financial resources and credibility more wisely, to manage production and stock costs more effectively, and to get to know customers better and reach them with the right strategies.

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Because now, they will know their customers better, they will be more successful in new product development and sales, they will motivate and coach their marketing teams, they will display a more realistic and skillful attitude in stock management, they will be able to manage real-time production operations much more effectively, they will be able to manage their financial resources. They know that they can use their creditworthiness and credibility more wisely, and that they can easily detect risks and frauds thanks to the accurate recording and processing of production, stock, sales and financial data.

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At this stage, we, with the "principle of confidentiality",

We can make it meaningful for you by making detailed studies and analyzes on your company's production and sales data.

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By reviewing your strategies accordingly, you can make decisions that lead to much more effective, efficient and profitable results.