Maci-D: An AI-powered tool to accelerate the identification and extraction of business intelligence data

在数据不断大量产生的时代，识别相关数据就像是大海捞针。咨询和研究公司为全球企业的决策提供支持。他们现在面临着管理数据报告、查找数据来源甚至重用处理过的数据的重大挑战。这影响了分析师的工作效率，他们支持的公司也因此错失了机会。为了应对这一挑战，Content Catalyst（一家商业智能发布软件开发公司）发现了一个机会，可以创建一个独特的解决方案，允许从分析师生成的报告中识别和提取数据。该解决方案将保留所有描述性信息，允许企业在适当的时间访问感兴趣的报告中的数据，确切地知道它来自何处，谁生成它以及何时生成它。Maci-D项目专注于研究各种先进计算技术的集成，以开发一个功能原型，使用户能够从数据报告中识别和提取数据。项目中生成的解决方案将使商业智能数据更易于访问和管理，从而增强其可重用性。描述性信息的保留将激励最终用户（英国/全球生成或消费研究报告的企业）采用更好的实践，例如参考，从而在他们的决策中重新获得信任。

In an age where data is generated continuously in large amounts, identifying relevant data has become equal to finding a needle in a haystack. Consultancies and research firms support decisions made by businesses worldwide. They now face a significant challenge to manage data reports, to find the source of data or even to re-use processed data. This impacts the productivity of analysts, and the companies they support miss on opportunities.To address this challenge, Content Catalyst, a software development company for business intelligence publishing, has identified an opportunity to create a unique solution that allows the identification and extraction of data from within reports generated by analysts. This solution will retain all descriptive information allowing businesses to access data from within reports of interest at the right time, knowing exactly where it came from, who generated it and when.Project Maci-D focuses on investigating the integration of various advanced computational technologies to develop a functional prototype that enables users to identify and extract data from within data reports.The solution generated in the project will allow business intelligence data to be more accessible and manageable, thus enhancing its re-use. The retention of descriptive information will motivate end-users (businesses in the UK/Worldwide generating or consuming research reports) to adopt better practices such as referencing, allowing trust to be regained in their decisions.