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.

本研究利用自由提供的芝加哥自行车共享数据集，采用 RTidyverse 库中的六个数据分析步骤来分析历史数据，从而向公司建议可行的方法来将临时骑行者转化为付费年度会员，为业界实际部署 BIA 技术提供了有价值的案例证明，并展示了数据分析周期的实践过程。