BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT

BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT

Table of Contents




Abstract

Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework.

Keywords

Business intelligence and analytics, big data analytics, Web 2.0

Introduction

Business intelligence and analytics (BI&A) and the related field of big data analytics have become increasingly important in both the academic and the business communities over the past two decades. Industry studies have highlighted this significant development. For example, based on a survey of over 4,000 information technology (IT) professionals from 93 countries and 25 industries, the IBM Tech Trends Report (2011) identified business analytics as one of the four major technology trends in the 2010s. In a survey of the state of business analytics by Bloomberg Business week (2011), 97 percent of companies with revenues exceeding $100 million were found to use some form of business analytics. A report by the McKinsey Global Institute (Manyika et al. 2011) predicted that by 2018, the United States alone will face a shortage of 140,000 to 190,000 people with deep analytical skills, as well as a shortfall of 1.5 million data-savvy managers with the know-how to analyze big data to make effective decisions.

Hal Varian, Chief Economist at Google and emeritus professor at the University of California, Berkeley, commented on the emerging opportunities for IT professionals and students in data analysis as follows:

So what’s getting ubiquitous and cheap? Data. And what is complementary to data? Analysis. So my recommendation is to take lots of courses about how to manipulate and analyze data: databases, machine learning, econometrics, statistics, visualization, and so on.

The opportunities associated with data and analysis in different organizations have helped generate significant interest in BI&A, which is often referred to as the techniques, technologies, systems, practices, methodologies, and applications that analyze critical business data to help an enterprise better understand its business and market and make timely business decisions. In addition to the underlying data processing and analytical technologies, BI&A includes business-centric practices and methodologies that can be applied to various high-impact applications such as e-commerce, market intelligence, e-government, healthcare, and security.

This introduction to the MIS Quarterly Special Issue on Business Intelligence Research provides an overview of this exciting and high-impact field, highlighting its many challenges and opportunities. Figure 1 shows the key sections of this paper, including BI&A evolution, applications, and emerging analytics research opportunities. We then report on a biblio metric study of critical BI&A publications, researchers, and research topics based on more than a decade of related BI&A academic and industry publications. Education and program development opportunities in BI&A are presented, followed by a summary of the six articles that appear in this special issue using our research framework. The final section concludes the paper.

Summary and Conclusions

Through BI&A 1.0 initiatives, businesses and organizations from all sectors began to gain critical insights from the structured data collected through various enterprise systems and analyzed by commercial relational database management systems. Over the past several years, web intelligence, web analytics, web 2.0, and the ability to mine unstructured user generated contents have ushered in a new and exciting era of BI&A 2.0 research, leading to unprecedented intelligence on consumer opinion, customer needs, and recognizing new business opportunities. Now, in this era of Big Data, even while BI&A 2.0 is still maturing, we find ourselves poised at the brink of BI&A 3.0, with all the attendant uncertainty that new and potentially revolutionary technologies bring.

This MIS Quarterly Special Issue on Business Intelligence Research is intended to serve, in part, as a platform and conversation guide for examining how the IS discipline can better serve the needs of business decision makers in light of maturing and emerging BI&A technologies, ubiquitous Big Data, and the predicted shortages of data-savvy managers and of business professionals with deep analytical skills. How can academic IS programs continue to meet the needs of their traditional students, while also reaching the working IT professional in need of new analytical skills? A new vision for IS may be needed to address this and other questions.

By highlighting several applications such as e-commerce, market intelligence, e-government, healthcare, and security, and by mapping important facets of the current BI&A knowledge landscape, we hope to contribute to future sources of knowledge and to augment current discussions on the importance of (relevant) academic research. Finally, the six papers chosen for this special issue are themselves a microcosm of the current state of BI&A research. These “best of the best” research papers showcase how high quality academic research can address real-world problems and contribute solutions that are relevant and long lasting— exactly the challenge that our discipline continues to face.

About KSRA

The Kavian Scientific Research Association (KSRA) is a non-profit research organization to provide research / educational services in December 2013. The members of the community had formed a virtual group on the Viber social network. The core of the Kavian Scientific Association was formed with these members as founders. These individuals, led by Professor Siavosh Kaviani, decided to launch a scientific / research association with an emphasis on education.

KSRA research association, as a non-profit research firm, is committed to providing research services in the field of knowledge. The main beneficiaries of this association are public or private knowledge-based companies, students, researchers, researchers, professors, universities, and industrial and semi-industrial centers around the world.

Our main services Based on Education for all Spectrum people in the world. We want to make an integration between researches and educations. We believe education is the main right of Human beings. So our services should be concentrated on inclusive education.

The KSRA team partners with local under-served communities around the world to improve the access to and quality of knowledge based on education, amplify and augment learning programs where they exist, and create new opportunities for e-learning where traditional education systems are lacking or non-existent.

FULL Paper PDF file:

BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT

Bibliography

author

Hsinchun Chen, Roger H. L. Chiang and Veda C. Storey

Year

2012

Title

Business Intelligence and Analytics: From Big Data to Big Impact

Publish in

Management Information Systems Research Center, University of Minnesota

DOI

PDF reference and original file: Click here

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Nasim Gazerani was born in 1983 in Arak. She holds a Master's degree in Software Engineering from UM University of Malaysia.

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Professor Siavosh Kaviani was born in 1961 in Tehran. He had a professorship. He holds a Ph.D. in Software Engineering from the QL University of Software Development Methodology and an honorary Ph.D. from the University of Chelsea.

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Somayeh Nosrati was born in 1982 in Tehran. She holds a Master's degree in artificial intelligence from Khatam University of Tehran.

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