With the improvement of people’s living standards and the emergence of aging society, the incidence of diabetes is increasing year by year, and diabetes and its complications have become the third killer threatening human health. There are many drugs for treating diabetes, but their toxic and side effects are all great. Therefore, using big data analysis to find and develop natural products with hypoglycemic effect has high practical value. Therefore, the purpose of this paper is to study the hypoglycemic effect of mulberry leaf extract based on big data analysis. Firstly, this paper studies the medicinal value of mulberry leaves and related application methods by consulting relevant data. Through big data analysis, it is found that mulberry leaves are rich in alkaloid component 1-deoxynojirimycin (DNJ), accounting for more than 50% of alkaloid content. Therefore, this paper takes mulberry leaf extract DNJ as the research object, and firstly prepares mulberry leaf extract. Mulberry leaf water extract was perfused into stomach for 15 consecutive days, and fasting blood glucose of diabetic mice was measured 2 hours after eating by glucose oxidase method at specified time. The hypoglycemic effect of mulberry leaf water extract was analyzed by big data. The results showed that mulberry leaf extract could effectively inhibit the enzyme activity of decomposing sugar and prevent glucose absorption. Therefore, it can significantly reduce the blood sugar level of diabetic mice by about 50%. And the higher the dose of mulberry leaf extract, the better the hypoglycemic effect, showing a dose effect.