Microsoft Azure Technology for Knowledge Mining
Azure, Microsoft’s cloud service platform, has a number of AI-related technologies, including the technology for knowledge mining (Knowledge Mining), which can effectively assist enterprises to process large amounts of data in the era of big data and obtain meaningful information in a short time To be analyzed. These data analysis results can help companies make more comprehensive and ideal business decisions, accelerate the pace of market development, and seize more business opportunities.
AI processing data trilogy
In the past, companies relied on manual analysis of massive data and extracted meaningful data from them to help them make decisions. Although OCR (Text Recognition) technology is sometimes applied to speed up the entire analysis process, when faced with increasing data and diversified data, the OCR technology alone has obviously not kept pace with the development speed. Now, through Microsoft Azure’s AI technology, enterprises can accurately analyze relevant data and obtain results in only three steps. First of all, AI will extract the data required by the enterprise from the messy and various types of information to analyze, and obtain the relationship between the data, and then enrich the meaning of the data, and finally the Automation is The enterprise outputs the desired results.
Third-party development tools
In addition to data analysis, companies can also develop different services through the core technology of Microsoft Azure to shorten the development process and focus on providing customers with better quality solutions. KBQuest, which is engaged in assisting the digital transformation of enterprises, has developed the Knowledge Mining product Ai-Knowie through Microsoft Azure, specializing in processing huge data for customers. The local online loan platform MoneySQ is one of the users adopting Ai-Knowie.
Through Ai-Knowie artificial intelligence approval, application documents submitted by customers, such as bank statements, proof of address, proof of work, etc., even if the data is scattered on multiple lines and pages, they will be systematically extracted and analyzed, thus Determine whether the customer’s income is stable, whether there are too many loans and bad consumption habits, and finally automatically make approvals and loans. If the documents provided by the customer are insufficient or there is a problem with the past records, Ai-Knowie will also make a suggestion to request the customer to add documents or ask the staff to approve again. For MoneySQ, automated credit approval not only helps to free up human resources, but also allows in-depth analysis of customer records to reduce human misjudgment.
Microsoft Azure Technology for Knowledge Mining - /10
Azure, Microsoft's cloud service platform, has a number of AI-related technologies, including the technology for knowledge mining.