The Application Of Time Series Analysis In Sales Data

This is an era full of large amounts of data.How to make use of these data is a problem that we should pay more and more attention to at present and in the future.Data mining technology is a good way to solve this problem.The core purpose of data mining is to find useful,potential and unknown information from a large number of disordered and non-connected data and provide decision support for different areas.In recent years,with the accumulation of large amounts of data,the research focus of data mining technology has gradually shifted from theoretical research to practical application,and focus on the integration of multiple discovery strategies and methods,and the mutual penetration between different disciplines.Data mining has attracted more and more attention in various industries and fields.After years of development,many companies have accumulated a large amount of sales data.But the processing of these sales data is just stay in the simple operation such as backup,query and statistics,and has no in-depth analysis and research.In fact,these sales data records can not only provide a certain degree of data support to the company's development plan,but also provide a reference for promotion assessing of the company's staff.It can also forecast a relatively reasonable sales performance for the company's sales staff.The application of data mining technology and methods to the company's sales data is of practical value and significance.In this paper,we first introduce some concepts and methods of data mining,then introduce the methods of using time series forecasting models anddata mining softwareWeka,and apply time series prediction methods to sales data.The paper also introduces the decision tree algorithm,which is applied to the prediction of sales potential.The main job is as follows:1)The time series forecasting methods based on exponential smoothing method and the SMOreg algorithm are used to predict the company's sales data,and the experimental results are analyzed.Experimental results show that an appropriatetime series forecasting model can predictsales targets more close to the actual sales.The forecast results can be used as a reference to the sales target of the sales staff,in order to reduce the situation that the sales target cannot be completed.A reasonable sales targets can reduce the phenomenon of sales staff to deposit or leave purchase orders.2)Based on the sales data table and the staff basic information table,the ID3 algorithm is used to build the decision tree to predict the sales potential of the sales staff,and the paper puts forward the corresponding suggestions.By forecasting sales potential,it can not only improve the success rate of hiring outstanding sales staff for companies but also provide reference for the sales staff to choose their jobs.