Reference no: EM133940476

Title: Big Data Analytics Services for Enhancing Business Intelligence

Abstract: This article examines how to use big data analytics services to enhance business intelligence (BI). More specifically, this article proposes an ontology of big data analytics and presents a big data analytics service-oriented architecture (BASOA), and then applies BASOA to BI, where our surveyed data analysis shows that the proposed BASOA is viable for enhancing BI and enterprise information systems. This article also explores temporality, expectability, and relativity as the characteristics of intelligence in BI. These characteristics are what customers and decision makers expect from BI in terms of systems, products, and services of organizations. The proposed approach in this article might facilitate the research and development of business analytics, big data analytics, and BI as well as big data science and big data computing.

Dataset:

- Gender of the participant surveyed on these topics
- Temporality: an average score of the rated ability to adapt to change over time 1 (not changing) to 7 (changing a lot)
- Expectability: a rated degree of satisfaction with the BI
- Relativity: average score rating of how much better one system is than another in BI 1 (not very good) to 7 (very good)
- Positive emotion: how positive participants felt about BI (higher scores are more positive, ranges from 1 to 7).

Missing:

a. Since any accuracy errors will create more than 5% missing data, exclude all data pairwise for the rest of the analyses.