Business Intelligence and Analytics: From Big Data …

1 SPECIAL ISSUE: Business Intelligence RESEARCHBUSINESS Intelligence AND Analytics: FROM BIG DATA TO BIG IMPACTH sinchun ChenEller College of Management, University of Arizona,Tucson, AZ 85721 H. L. ChiangCarl H. Lindner College of Business , University of Cincinnati,Cincinnati, OH 45221-0211 C. StoreyJ. Mack Robinson College of Business , Georgia State University,Atlanta, GA 30302-4015 Intelligence and analytics (BI&A) has emerged as an important area of study for both practitionersand researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporarybusiness organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Researchfirst provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A , BI&A , and BI&A are defined and described in terms of their key characteristics andcapabilities.

2 Current research in BI&A is analyzed and challenges and opportunities associated with BI&Aresearch 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 , the six articles that comprise this special issue are introduced and characterized in terms of theproposed BI&A research : Business Intelligence and analytics , big data analytics , Web Intelligence and analytics (BI&A) and the relatedfield of big data analytics have become increasingly importantin both the academic and the Business communities over thepast two decades. Industry studies have highlighted thissignificant development. For example, based on a survey ofover 4,000 information technology (IT) professionals from 93countries and 25 industries, the IBM Tech Trends Report(2011) identified Business analytics as one of the four majortechnology trends in the 2010s.

3 In a survey of the state ofbusiness analytics by Bloomberg Businessweek (2011), 97percent of companies with revenues exceeding $100 millionwere found to use some form of Business analytics . A reportby the McKinsey Global Institute (Manyika et al. 2011) pre-dicted that by 2018, the United States alone will face a short-age of 140,000 to 190,000 people with deep analytical skills,as well as a shortfall of million data-savvy managers withthe know-how to analyze big data to make effective Varian, Chief Economist at Google and emeritus profes-sor at the University of California, Berkeley, commented onthe emerging opportunities for IT professionals and studentsin data analysis as follows:MIS Quarterly Vol. 36 No. 4, pp. 1165-1188/December 2012 1165 Chen et : Business Intelligence ResearchSo what s getting ubiquitous and cheap? Data. Andwhat is complementary to data?

4 Analysis. So myrecommendation is to take lots of courses about howto manipulate and analyze data: databases, machinelearning, econometrics, statistics, visualization, andso opportunities associated with data and analysis in dif-ferent organizations have helped generate significant interestin BI&A, which is often referred to as the techniques, tech-nologies, systems, practices, methodologies, and applicationsthat analyze critical Business data to help an enterprise betterunderstand its Business and market and make timely businessdecisions. In addition to the underlying data processing andanalytical technologies, BI&A includes Business -centricpractices and methodologies that can be applied to varioushigh-impact applications such as e-commerce, market intelli-gence, e-government, healthcare, and introduction to the MIS Quarterly Special Issue onBusiness Intelligence Research provides an overview of thisexciting and high-impact field, highlighting its many chal-lenges and opportunities.

5 Figure 1 shows the key sectionsof this paper, including BI&A evolution, applications, andemerging analytics research opportunities. We then reporton a bibliometric study of critical BI&A publications,researchers, and research topics based on more than a decadeof related BI&A academic and industry publications. Educa-tion and program development opportunities in BI&A arepresented, followed by a summary of the six articles thatappear in this special issue using our research final section concludes the Evolution: Key Characteristicsand CapabilitiesThe term Intelligence has been used by researchers inartificial Intelligence since the 1950s. Business intelligencebecame a popular term in the Business and IT communitiesonly in the 1990s. In the late 2000s, Business analytics wasintroduced to represent the key analytical component in BI(Davenport 2006).

6 More recently big data and big dataanalytics have been used to describe the data sets and ana-lytical techniques in applications that are so large (fromterabytes to exabytes) and complex (from sensor to socialmedia data) that they require advanced and unique datastorage, management, analysis, and visualization technol-ogies. In this article we use Business Intelligence and ana-lytics (BI&A) as a unified term and treat big data analytics asa related field that offers new directions for BI&A a data-centric approach, BI&A has its roots in the long-standing database management field. It relies heavily onvarious data collection, extraction, and analysis technologies(Chaudhuri et al. 2011; Turban et al. 2008; Watson andWixom 2007). The BI&A technologies and applicationscurrently adopted in industry can be considered as BI&A ,where data are mostly structured, collected by companiesthrough various legacy systems, and often stored in commer-cial relational database management systems (RDBMS).

7 Theanalytical techniques commonly used in these systems,popularized in the 1990s, are grounded mainly in statisticalmethods developed in the 1970s and data mining techniquesdeveloped in the 1980s. Data management and warehousing is considered the foun-dation of BI&A Design of data marts and tools forextraction, transformation, and load (ETL) are essential forconverting and integrating enterprise-specific data. Databasequery, online analytical processing (OLAP), and reportingtools based on intuitive, but simple, graphics are used toexplore important data characteristics. Business performancemanagement (BPM) using scorecards and dashboards helpanalyze and visualize a variety of performance metrics. Inaddition to these well-established Business reporting func-tions, statistical analysis and data mining techniques areadopted for association analysis, data segmentation andclustering, classification and regression analysis, anomalydetection, and predictive modeling in various Business appli-cations.

8 Most of these data processing and analytical tech-nologies have already been incorporated into the leading com-mercial BI platforms offered by major IT vendors includingMicrosoft, IBM, Oracle, and SAP (Sallam et al. 2011). Among the 13 capabilities considered essential for BI plat-forms, according to the Gartner report by Sallam et al. (2011),the following eight are considered BI&A : reporting,dashboards, ad hoc query, search-based BI, OLAP, interactivevisualization, scorecards, predictive modeling, and datamining. A few BI&A areas are still under active devel-opment based on the Gartner BI Hype Cycle analysis foremerging BI technologies, which include data mining work-benchs, column-based DBMS, in-memory DBMS, and real-time decision tools (Bitterer 2011). Academic curricula inInformation Systems (IS) and Computer Science (CS) often1 Hal Varian Answers Your Questions, February 25, 2008 ( ).

9 1166 MIS Quarterly Vol. 36 No. 4/December 2012 Chen et : Business Intelligence ResearchFigure 1. BI&A Overview: Evolution, Applications, and Emerging Researchinclude well-structured courses such as database managementsystems, data mining, and multivariate the early 2000s, the Internet and the Web began to offerunique data collection and analytical research and develop-ment opportunities. The HTTP-based Web systems,characterized by Web search engines such as Google andYahoo and e-commerce businesses such as Amazon andeBay, allow organizations to present their businesses onlineand interact with their customers directly. In addition toporting their traditional RDBMS-based product informationand Business contents online, detailed and IP-specific usersearch and interaction logs that are collected seamlesslythrough cookies and server logs have become a new goldmine for understanding customers needs and identifying newbusiness opportunities.

10 Web Intelligence , web analytics , andthe user-generated content collected through Web and crowd-sourcing systems (Doan et al. 2011;O Reilly 2005) have ushered in a new and exciting era ofBI&A research in the 2000s, centered on text and webanalytics for unstructured web immense amount of company, industry, product, andcustomer information can be gathered from the web andorganized and visualized through various text and web miningtechniques. By analyzing customer clickstream data logs,web analytics tools such as Google analytics can provide atrail of the user s online activities and reveal the user sbrowsing and purchasing patterns. Web site design, productplacement optimization, customer transaction analysis, marketstructure analysis, and product recommendations can beaccomplished through web analytics .