The data revolution experienced in recent times has thrown up new challenges and opportunities for businesses of all sizes in diverse industries. Big data analytics is already at the forefront of innovations to help make meaningful business decisions from the abundance of raw data available today. Business intelligence and analytics has become a huge trend in todays IT world as companies of all sizes are looking to improve their business processes and scale up using data driven solutions. This paper aims to demonstrate the data analytical process of deriving business intelligence via the historical data of a fictional bike share company seeking to find innovative ways to convert their casual riders to annual paying registered members. The dataset used is freely available as Chicago Divvy Bicycle Sharing Data on Kaggle. The authors used the RTidyverse library in RStudio to analyse the data and followed the six data analysis steps of ask, prepare, process, analyse, share, and act to recommend some actionable approaches the company could adopt to convert casual riders to paying annual members. The findings from this research serve as a valuable case example, of a real world deployment of BIA technologies in the industry, and a demonstration of the data analysis cycle for data practitioners, researchers, and other potential users.

翻译：近期经历的数据革命为不同行业、各种规模的企业带来了新的挑战与机遇。大数据分析已处于创新前沿，助力从当今海量原始数据中做出有意义的商业决策。商业智能与分析已成为当今IT世界的一大趋势，各类企业都希望借助数据驱动的解决方案优化业务流程并实现规模化发展。本文旨在通过虚构的共享单车公司的历史数据，演示从数据中提取商业智能的分析过程——该公司正寻求创新方式将休闲骑行者转化为年度付费注册会员。使用的数据集为芝加哥迪维共享单车数据，可从Kaggle免费获取。作者利用RStudio中的RTidyverse库对数据进行分析，遵循"提问、准备、处理、分析、分享、行动"六步数据分析流程，提出该公司可采纳的可行举措以转化休闲骑手为付费年度会员。本研究结果可作为商业智能与分析技术在行业中实际部署的典型案例，同时为数据从业者、研究人员及其他潜在用户展示数据分析全周期。