Big Data Analytics: Opportunity Or Threat For Accounting And Supply Chain Management

Structured/Unstructured Data and Issue-driven/Exploratory Analysis

Discuss about the Annotated Bibliography for Measurement and Management.

Reference 1:

Richins, G., Stapleton, A., Stratopoulos, T. C., & Wong, C. (2017). Big Data Analytics: Opportunity or Threat for the Accounting Profession?. Journal Of Information Systems, 31(3), 63-79. doi:10.2308/isys-51805

As opposed to Frey and Osborne’s (2013) forecast that the bookkeeping profession faces eradication, we contend that accountants can, in any case, make an incentive in a universe of Big Data analytics. To propel this position, we give a conceptual framework given organized/unstructured data and issue-driven/exploratory examination. We contend that accountants as of now exceed expectations at issue driven investigation of organized data, are very much situated to assume the main part in the issue-driven examination of unstructured data, and can bolster data researchers performing an exploratory investigation on Big Data.

Reference 2:

The Impact of Maintenance 4.0 and Big Data Analytics within Strategic Asset Management. (2017). MPMM 2016, Maintenance, Performance, Measurement & Management: conference proceedings, 96.

The most recent mechanical upset is showed by smart and networking hardware. Understanding the full estimation of these apparatuses, and different business assets have turned out to be progressively essential. Strategic asset management faces administrative, specialized and also methodological difficulties, of which some could be lessened or overwhelmed by applying mechanical arrangements, for example, Internet of things, distributed computing, digital physical frameworks and big data analytics. This paper plots the effect of the developing advancements in the zone of strategic management with extreme accentuation on the analytics as a specialist co-op for the support capacities.

Reference 3:

Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the Use of Big Data Analytics Affects Value Creation in Supply Chain Management. Journal Of Management Information Systems, 32(4), 4-39. doi:10.1080/07421222.2015.1138364

In spite of various tributes of first movers, the hidden instruments of associations’ big data analytics (BDA) utilization merit close examination. Our examination tends to two fundamental research questions: (1) How does hierarchical BDA use influence esteem creation? And (2) What are critical forerunners of authoritative level BDA utilization? We draw on powerful abilities hypothesis to conceptualize BDA use as an exceptional data preparing capacity that conveys upper hand to associations. Moreover, we utilize the technology– organization– condition (TOE) framework to distinguish and guess ways through which factors impact the genuine use of BDA. Study data gathered from 161 U.S.- based organizations demonstrate that: authoritative level BDA utilization influences hierarchical esteem creation; how much BDA use impacts such production is directed by environmental dynamism; mechanical factors straightforwardly impact authentic BDA use, and hierarchical and natural factors by implication impact hierarchical BDA use through best management bolster.

Maintenance 4.0 and Big Data Analytics in Strategic Asset Management

Reference 4:

Sanders, N. R. (2016). How to Use Big Data to Drive Your Supply Chain. California Management Review, 58(3), 26-48.

Big data analytics has turned into a basis for business pioneers over each industry part. Analytics applications that can convey an upper hand seem up and down the supply chain choice range – from the focused area based showcasing to improving supply chain inventories to empowering provider chance appraisal. While numerous organizations have utilized it to remove new bits of knowledge and make new types of significant worth, different organizations still can’t seem to use big data to change their supply chain operations. This article analyzes how driving organizations utilize big data analytics to drive their supply chains and offers a framework for execution in light of lessons learned.

Reference 5:

Biju, S. M., & Mathew, A. (2017). COMPARATIVE ANALYSIS OF SELECTED BIG DATA ANALYTICS TOOLS. Journal Of International Technology & Information Management, 26(2), 2-22.

In the course of the most recent couple of years, big data has risen as an essential subject of discourse in many firms attributable to its capacity of creation, stockpiling and handling of substance at a reasonable cost. Big data comprises of cutting-edge devices and systems to process vast volumes of data in associations. Interest in big data analytics has nearly turned into a need in large measured firms, especially multinational organizations, for its exceptional advantages, especially in the forecast and distinguishing proof of different patterns. The simple most mainstream big data analytics programming utilized today are MapReduce, Hive, Tableau, and Hive, while the framework Hadoop empowers simple preparing of such exceedingly substantial data sets. The momentum inquires about endeavors to make a relative appraisal of five such applications, in particular, IBM SPSS, IBM Watson Analytics, R, Minitab, and SAS. The case produced results of the test was that of the elements influencing housing reasonableness in the US. In light of the measurements got from the American Housing Survey (AHS) database, the analyst has distinguished distinctive components affecting the reasonableness in the states. The procedure of diminishing factors, however, Principal Component Analysis (PCA) and a model in light of halfway minimum square relapse/polynomial relapse were fitted to check the effect on the moderateness. The essential discoveries recommend that significantly age of the leader of the family, salary earned were the two most important variables influencing the estimating in the locale. Likewise, a correlation is drawn toward the finish of concentrate with an understanding of the most and minimum compelling applications

The Use of Big Data Analytics in Supply Chain Management

Reference 6:

Dremel, C., Wulf, J., Herterich, M. M., Waizmann, J., & Brenner, W. (2017). How AUDI AG Established Big Data Analytics in Its Digital Transformation. MIS Quarterly Executive, 16(2), 81-100.

Digital transformation, which frequently incorporates setting up big data analytics capacities, postures significant difficulties for customary assembling associations, for example, auto organizations. Efficiently presenting big data analytics requires substantial hierarchical transformation and new authoritative structures and business forms. Given the three-arrange development of big data analytics abilities at AUDI, we give proposals to how customary assembling associations can effectively present big data analytics and ace the related authoritative transformations.

Reference 7:

Henry, R., & Venkatraman, S. (2015). BIG DATA ANALYTICS THE NEXT BIG LEARNING OPPORTUNITY. Academy Of Information & Management Sciences Journal, 18(2), 17-29.

The tireless gathering of data from client associations in sites has presented both an abnormal state of many-sided quality, and also an incredible open door for organizations. Furthermore, the pattern of interfacing individuals, as well as machines to the Internet, and then gathering data from these machines through sensors would soon bring about an incredible storehouse of data. This consistently expanding gathering of data, otherwise called Big Data, may be helpful on the off chance that it can be broken down to give valuable experiences to business issues, and maybe even to influence proposals with reference to when and where future matters to will happen (predictive analytics) so the problems can be evaded or if nothing else alleviated. Understudies must be readied exploit for next open doors in the field of big data analytics. In many business programs, particularly data framework as the real, center course like database plan, office applications, and essential writing computer programs are educated to students. A fundamental part missing from numerous undergrad business programs are center courses concentrating on data analytics. The US Department of Labor predicts 4.4 million open doors will exist by 2018, working with data analytics.

Reference 8:

Metcalf, J. (2016). Big Data Analytics and Revision of the Common Rule. Communications Of The ACM, 59(7), 31-33. doi:10.1145/2935882

The article talks about conceivable changes to the Common Rule in inquiring about morals because of the development of big data analytics. Points incorporate a September 2015 Notice of Proposed Rule-Making (NPRM) issued by the U.S. Branch of Health and Human Services (HHS), the qualification amongst training and research in connection to the 1979 Belmont Report on human subject research, and the proper class of freely accessible datasets containing private data.

Comparative Analysis of Selected Big Data Analytics Tools

Reference 9:

Cloud computing for big data analytics in the Process Control Industry. (2017). Mediterranean Conference on Control and Automation 2017 25th Mediterranean Conference on Control and Automation, MED 2017, 1373. doi:10.1109/MED.2017.7984310

The point of this article is to show a case of a novel cloud computing foundation for big data analytics in the Process Control Industry. Most recent developments in the field of Process Analyzer Techniques (PAT), big data and remote advances have made another condition in which all phases of the mechanical procedure can be recorded and used, for wellbeing, as well as for continuous enhancement. Given investigation of recorded sensor data, machine learning based streamlining models can be produced and conveyed progressively shut control circles. Be that as it may, in any case, the neighborhood execution of those frameworks requires an immense interest in equipment and programming, as an immediate consequence of the big data nature of sensors data being recorded consistently. The current mechanical progressions in cloud computing for big data processing, open new open doors for the industry while going about as an empowering influence for a noteworthy diminishment in costs, making the technology accessible to plants of all sizes. The principle commitment of this article comes from the introduction of a clench hand time ever of a pilot cloud-based engineering for the use of a data-driven demonstrating an ideal control design for the field of Process Control. As it will be displayed, these advancements have been conveyed in cozy association with the procedure industry and clear a route for a summed up use of the cloud-based methodologies, towards the fate of Industry 4.0

Reference 10:

Digital Service Innovation Enabled by Big Data Analytics: A Review and the Way Forward. (2017). Proceedings of the 50th Hawaii International Conference on System Sciences 2017,

Service innovation is drawing in consideration with the expanding service enterprises and economies. Joined by real improvements in ICT and real and digital advancements, the enthusiasm for digital service innovation (DSI), both from the scholarly community and industry, is expanding. Digitization and the going with mechanical progressions are prompting wonders that call for extensive research in connection to service innovation; one of which is Big data analytics (BDA). In this paper, we survey the DSI writing and investigate how BDA can contribute along the distinctive measurements of DSI. The ex-post writing experiences the absence of such examinations. Appropriately, we recommend an exploration plan for BDA-empowered DSI, spurred by emerging examination holes, and also openings and directing exploration questions.

Wedel, M., & Kannan, P. K. (2016). Marketing Analytics for Data-Rich Environments. Journal Of Marketing, 80(6), 97-121. doi:10.1509/jm.15.0413

The creators give a basic examination of marketing analytics strategies by following their recorded advancement, looking at their applications to organized and unstructured data produced inside or outer to a firm, and evaluating their capability to help marketing choices. The creators recognize headings for new systematic research techniques, tending to (1) analytics for improving marketing-blend spending in a data-rich condition, (2) analytics for personalization, and (3) analytics with regards to clients’ protection and data security. They survey the suggestions for associations that mean to execute big data analytics. At long last, swinging to the future, the creators distinguish patterns that will shape marketing analytics as a train and also market analytics instruction.

Reference 12:

Lawler, J., & Joseph, A. (2017). Big Data Analytics Methodology in the Financial Industry. Information Systems Education Journal, 15(4), 38-51.

Firms in the industry keep on being pulled in by the advantages of Big Data Analytics. The benefits of Big Data Analytics undertakings may not be as apparent as much of the time demonstrated in writing. The creators of the investigation assess factors in an altered procedure that may build the advantages of Big Data Analytics ventures. Evaluating firms in the budgetary industry, the creators find that business and procedural elements, for example, joint effort development of the association and Big Data Analytics administration, are more critical than the subtleties of technology, for example, equipment and item programming of technology firms, in starting to amplify the capability of Big Data Analytics in the organizations. The discoveries of the paper will profit instructors in enhancing Big Data Analytics curricular projects to be present with the examples of firms productively starting Big Data Analytics systems.