System of predicting, analyzing and displaying information index

Abstract

The invention discloses a system of predicting, analyzing and displaying an information index. The system comprises a prediction and comparison unit and a data combination unit, wherein the prediction and comparison unit is used for predicting a future information index and carrying out comparison display on a plurality of prediction results; the data combination unit is used for making the information index or historical data, client quantification prediction data, a client or client team qualitative analysis and a final action countermeasure form iterative combined display of information history, prediction and the action countermeasure and providing a previous iterative combined display searching function. Future prediction and historical analysis can be effectively performed on the information index.

Description

technical field [0001] The invention relates to the field of information index prediction, in particular to a system for predicting, analyzing and displaying information index. Background technique [0002] At present, for the information index that enterprises care about, a small number of large customers use enterprise information integration software such as DSS, MIS or BI, and most small and micro enterprises or individuals use data reports or documents to store the original data of the information index and make future predictions and historical analysis. [0003] Specifically, the customer manually enters the information index released by the third-party information platform into the enterprise information integration software of the customer's enterprise or personal data reports or documents. Automatic calculation of historical data through the calculation functions of the above software, reports or documents combined with the analysis method designed by the customer...

AI Technical Summary

Problems solved by technology

[0004] The problems with the above-mentioned future prediction and historical analysis methods are: (1) Customers cannot publish their own information index to a third-party platform to form a benchmark index, and at the same time, it can be seen by the customer itself or other business-related multiple customers. Visible way to predict the future

(2) For the information index released by the third-party platform or the customer itself, the customer cannot freely choose to predict the future data with the customer's own future under the premise of data compatibility in different storage environments such as the customer server, third-party platform or cloud. Compute, search, display and upload with or without options

(3) It is impossible to describe the future forecast data and graphics of customer satisfaction by simply sliding your finger without typing any numbers

Unable to achieve online comparative display of multiple customers

(4) Customers have to update or record their own future forecasts in traditional ways on a daily basis. It is impossible to realize the combined display of iterative information forecasts that automatically update the historical data of the information index and customer forecast data on a daily basis. The above-mentioned combined display cannot be realized For the iterative merged display of the above-mentioned information history, forecast and action countermeasures, it is impossible to summarize and search for the past iterative merged display

(5) It is impossible to quantitatively describe the level of future predictions of different customers for the same benchmark index, and it is impossible to automatically notify the above-mentioned level to interested third-party customers

Due to the lack of quantitative historical evaluation of each customer's future forecast for a given benchmark index, the enterprise itself or its customers cannot judge who is better and who is worse

The inoperability of this kind of judgment is the reason for the impurity in the enterprise or the dispute between the superior and the superior.

As a result, traditional future forecasting and historical analysis not only fail to provide assistance to enterprises or customers in decision-making, but sometimes poison the decision-making or reduce efficiency of enterprises due to poor experience and poor operability.

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