Secondary data, customer databases and big data analytics

AbstractOver the last few decades Big Data has impetuously penetrated almost every domain of human interest/action and it has (more or less consciously) become a ubiquitous presence of day to day life. The main questions this exploratory paper seeks to address (throughout its two parts) are the following: What is the (actual) impact of Big Data on Business & Management and How can businesses (through their management) leverage the potential of Big Data to their benefit? A gradual, step by step approach (based on literature review and a variety of secondary data) will guide the paper in search for answers to the abovementioned questions: starting with a concise history of the topic Big Data as reflected in academia and a critical content analysis of the Big Data concept, the paper will then continue by emphasizing some of the most significant realities and trends that characterize the supply-side of the big data industry; the second part of the paper is dedicated to the investigation of the demand-side of the big data industry – by highlighting some evidences (and projections) on the impact of big data analytics on Business & Management (both at aggregate and granular level) and exploring what companies could and should do (through their management) in order to best capitalize on the opportunities of big data and avoid/minimize the impact of its threats.

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An Analysis of Big Data Analytics, IoT and Augmented Banking on Consumer Loan Banking Business in Germany

Journal of Research on Business and Tourism ◽

10.37535/104001120212 ◽

2021 ◽

Vol 1 (1) ◽

pp. 16

Author(s):

Maulibian Putra

Keyword(s):

Big Data ◽

Internet Of Things ◽

Industry 4.0 ◽

Data Analytics ◽

Big Data Analytics ◽

Secondary Data ◽

Academic Literature ◽

Consumer Loans ◽

Banking Business ◽

Data Analytic

This research aims to analyze the particular component of industry 4.0 applying in the consumer loans banking business. Industry 4.0 comprises of a lot of technological advantages, this research selected three components of industry 4.0; Big data analytic, Internet of Things (IoT), and Augmented reality in banking. Secondary data are used to conduct this research, collected from the previous research and the academic literature. At first, this research explains why the consumer loans banking business in Europe, especially in Germany, needs to integrate Industry 4.0. secondly, this research analyzes the suitable component of industry 4.0 into the consumer loans banking business. The findings of this research deliver an essential piece of analysis to the consumer loans banking business' stakeholder with direction on implementing industry 4.0 into their business.

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Big Data Issues and Challenges

Advances in Library and Information Science - Big Data Applications for Improving Library Services ◽

10.4018/978-1-7998-3049-8.ch001 ◽

2021 ◽

pp. 1-21

Author(s):

Shweta Kaushik

Keyword(s):

Big Data ◽

Data Storage ◽

Academic Libraries ◽

Data Analytics ◽

Big Data Analytics ◽

Secondary Data ◽

Vital Role ◽

Information Visualisation ◽

Central Data

The library plays a vital role for the students, researchers, and academician as a central data storage which is utilized for accessing any required data within less time and effort. Academic libraries are rich in primary and secondary data with lots of content, which may include data from other resources also such as internet and other media. This large amount of data must provide a valuable information to the user, but it may not be same format. Librarians need to transform and analyse all the available data to the same format so that it becomes easier for the user to facilitate the required knowledge. For example, they need to create a dataset in a manner that is easy to visualize and accessible. In this regard, big data analytics tools such as information visualisation tools help the user in mining the intended information. In any case, it is assumed that the confinements and conceivable outcomes of Big data innovation are being considered and that relationships are acknowledged as precise. This chapter focus on all the possibilities of various issues and challenges that may arise while using big data with library.

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Big Data Analytics: The Next Big Thing

The Management Accountant Journal ◽

10.33516/maj.v54i5.20-24p ◽

2019 ◽

Vol 54 (5) ◽

pp. 20

Author(s):

Dheeraj Kumar Pradhan

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics

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Strategy in Discovery Mode - Wie Big Data & Analytics strategisches Denken verdrängen kann

WiSt - Wirtschaftswissenschaftliches Studium ◽

10.15358/0340-1650-2020-5-11 ◽

2020 ◽

Vol 49 (5) ◽

pp. 11-17

Author(s):

Thomas Wrona ◽

Pauline Reinecke

Keyword(s):

Big Data ◽

Data Analytics ◽

Big Data Analytics

Big Data & Analytics (BDA) ist zu einer kaum hinterfragten Institution für Effizienz und Wettbewerbsvorteil von Unternehmen geworden. Zu viele prominente Beispiele, wie der Erfolg von Google oder Amazon, scheinen die Bedeutung zu bestätigen, die Daten und Algorithmen zur Erlangung von langfristigen Wettbewerbsvorteilen zukommt. Sowohl die Praxis als auch die Wissenschaft scheinen geradezu euphorisch auf den „Datenzug“ aufzuspringen. Wenn Risiken thematisiert werden, dann handelt es sich meist um ethische Fragen. Dabei wird häufig übersehen, dass die diskutierten Vorteile sich primär aus einer operativen Effizienzperspektive ergeben. Strategische Wirkungen werden allenfalls in Bezug auf Geschäftsmodellinnovationen diskutiert, deren tatsächlicher Innovationsgrad noch zu beurteilen ist. Im Folgenden soll gezeigt werden, dass durch BDA zwar Wettbewerbsvorteile erzeugt werden können, dass aber hiermit auch große strategische Risiken verbunden sind, die derzeit kaum beachtet werden.

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