Intelligent analysis can clearly see the data search and analysis process at

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Problems like this arise in endlessly in practical applications and companies gradually realize that dialogue is only a form not a result. Simple search cannot guarantee the rationality of the data. To prevent the data from becoming sourceless water the analysis process must be increased. Therefore using reasoning capabilities breaks down the barriers to analysis and opens the second stage of intelligence. To put it simply intelligent analysis means that the BI system can proactively identify problems conduct root cause analysis and provide solution suggestions.


This requires the BI system to accumulate a large amount of domain know Job Seekers Phone Numbers List ledge and complex reasoning capabilities. Some manufacturers represented by Aisu are working on knowledge graphs and large models to try in this direction. Li Jiliang vice president of Aishu Products told Guangcone Intelligence Only through knowledge can we do technical correlation analysis. For example when the statistical caliber of the data is inconsistent the understanding ability of a large model is required to understand the data with similar meaning and organize and classify it.





To give a simple example: For employees with a bachelors degree or above in a statistics company this is not about keyword screening but about understanding the three specific degrees: bachelors degree masters degree and doctoral degree. At the analysis layer traditional BI software can display abnormal fluctuations in data such as sluggish sales in October.  each step through the regression analysis model and the result attribution can be drilled down layer by layer. Break it down one by one and then use ChatBI to show whether the influencing factors are brands customers or channels. Looking one step further reshaping the BI system through intelligent agents may be the third stage of intelligence. The concept of Agent has become popular recently.