TY - GEN
T1 - Using Data Analytics to Derive Business Intelligence
T2 - International Conference on Cybersecurity, Situational Awareness and Social Media, CYBER SCIENCE 2023
AU - Orji, Ugochukwu
AU - Obianuju, Ezugwu
AU - Ezema, Modesta
AU - Ugwuishiwu, Chikodili
AU - Ukwandu, Elochukwu
AU - Agomuo, Uchechukwu
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024/2/18
Y1 - 2024/2/18
N2 - 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 (BIA) has become a huge trend in today’s 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 R-Tidyverse library in RStudio to analyze the data and followed the six data analysis steps of; ask, prepare, process, analyze, 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.
AB - 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 (BIA) has become a huge trend in today’s 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 R-Tidyverse library in RStudio to analyze the data and followed the six data analysis steps of; ask, prepare, process, analyze, 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.
KW - Big data analytics
KW - Business intelligence
KW - Data analysis cycle
KW - Data analytics
UR - http://www.scopus.com/inward/record.url?scp=85187770958&partnerID=8YFLogxK
U2 - 10.1007/978-981-99-6974-6_3
DO - 10.1007/978-981-99-6974-6_3
M3 - Conference contribution
AN - SCOPUS:85187770958
SN - 9789819969739
T3 - Springer Proceedings in Complexity
SP - 35
EP - 46
BT - Proceedings of the International Conference on Cybersecurity, Situational Awareness and Social Media - Cyber Science 2023
A2 - Onwubiko, Cyril
A2 - Rosati, Pierangelo
A2 - Rege, Aunshul
A2 - Erola, Arnau
A2 - Bellekens, Xavier
A2 - Hindy, Hanan
A2 - Jaatun, Martin Gilje
PB - Springer Science and Business Media B.V.
Y2 - 3 July 2023 through 4 July 2023
ER -