scholarly journals Understanding the Data Science behind Business Analytics

2017 ◽  
pp. 93-116 ◽  
Author(s):  
Mayank Mishra ◽  
Pratik Mishra ◽  
Arun K. Somani
Keyword(s):  
Data Science ◽  
Business Analytics

The Context of IST for Solid Information Retrieval and Infrastructure Building

2021 ◽  
pp. 2040-2054
Author(s):  
Prantosh Kumar Paul
Keyword(s):  
Developing Countries ◽  
Information Technologies ◽  
Data Science ◽  
Information Science ◽  
Swot Analysis ◽  
Vital Role ◽  
Knowledge Dissemination ◽  
Business Analytics ◽  
Limited Information ◽  
Information Sciences

Development and progress mainly depends on education and its solid dissemination. Technologies as well as engineering solutions are important for the business and corporate houses. In this context, educational initiatives and programs play a vital role. Developing countries are suffering from many problems and therefore fostering new academic innovation and researches on economic development in today's context. Information Technologies and management science are important for solid business solutions. Therefore, education and knowledge dissemination play an important and valuable role. In many developing countries, gaps between industrial needs and the availability of skilled labor are limited. Information Sciences and Computing are the most valuable areas of study in today's knowledge world. The components, subsets, and subfields of Information Sciences and Technology are rapidly emerging worldwide. Among the emerging and popular areas, a few include Cloud Computing, Green Computing, Green Systems, Big-Data Science, Internet, Business Analytics, and Business Intelligence. Developing countries (like China, Colombia, Malaysia, Mauritius, India, Brazil, South Africa) depend in many ways on knowledge dissemination and solid manpower for their development. Thus, there is an urgent need to introduce such programs and the majority of these programs have been proposed here. Information Science and Technology (IST) with programs such as Bachelors, Masters, and Doctoral Degrees have been listed here with academic and industrial contexts. This article highlights these programs with proper SWOT analysis.

Data Science for Business Analytics and Business Intelligence

2021 ◽  
pp. 495-508
Author(s):  
Matthias Lederer ◽  
Patrick Schmid
Keyword(s):  
Business Intelligence ◽  
Data Science ◽  
Digital Data ◽  
Competitive Advantages ◽  
Business Analytics ◽  
Simulation And Optimization ◽  
Analytical Skills ◽  
Methods And Techniques ◽  
Different Levels

Data science as the interdisciplinary collection of methods and techniques to support businesses is becoming more and more popular. This article begins with definitions and shows how systematically competitive advantages can be built up on the basis of digital data. Essential sources and types of data-driven knowledge are introduced. Then a classification of approaches of data science concepts is explained. A distinction is made between Business Analytics and Business Intelligence as different levels of analytical skills. The paper goes into depth with these concepts and presents concrete techniques, algorithms, and application scenarios. Thus, the contribution introduces State of the Art approaches to analysis, control, monitoring but also to advanced approaches such as prediction, simulation, and optimization.

The Nature of Intelligent Analytics

2021 ◽  
pp. 1-21
Author(s):  
Zhaohao Sun ◽  
Andrew Stranieri
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Research And Development ◽  
Business Intelligence ◽  
Data Analytics ◽  
Data Science ◽  
Big Data Analytics ◽  
Business Analytics ◽  
Novel Approach ◽  
Advanced Analytics

Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.

The Context of IST for Solid Information Retrieval and Infrastructure Building

2018 ◽  
Vol 8 (1) ◽  
pp. 86-100
Author(s):  
Prantosh Kumar Paul
Keyword(s):  
Developing Countries ◽  
Information Technologies ◽  
Data Science ◽  
Information Science ◽  
Swot Analysis ◽  
Vital Role ◽  
Knowledge Dissemination ◽  
Business Analytics ◽  
Limited Information ◽  
Information Sciences

Development and progress mainly depends on education and its solid dissemination. Technologies as well as engineering solutions are important for the business and corporate houses. In this context, educational initiatives and programs play a vital role. Developing countries are suffering from many problems and therefore fostering new academic innovation and researches on economic development in today's context. Information Technologies and management science are important for solid business solutions. Therefore, education and knowledge dissemination play an important and valuable role. In many developing countries, gaps between industrial needs and the availability of skilled labor are limited. Information Sciences and Computing are the most valuable areas of study in today's knowledge world. The components, subsets, and subfields of Information Sciences and Technology are rapidly emerging worldwide. Among the emerging and popular areas, a few include Cloud Computing, Green Computing, Green Systems, Big-Data Science, Internet, Business Analytics, and Business Intelligence. Developing countries (like China, Colombia, Malaysia, Mauritius, India, Brazil, South Africa) depend in many ways on knowledge dissemination and solid manpower for their development. Thus, there is an urgent need to introduce such programs and the majority of these programs have been proposed here. Information Science and Technology (IST) with programs such as Bachelors, Masters, and Doctoral Degrees have been listed here with academic and industrial contexts. This article highlights these programs with proper SWOT analysis.

scholarly journals Business Analytics and Data Science: Once Again?

2016 ◽  
Vol 59 (2) ◽  
pp. 77-79 ◽  
Author(s):  
Martin Bichler ◽  
Armin Heinzl ◽  
Wil M. P. van der Aalst
Keyword(s):  
Data Science ◽  
Business Analytics

Foreword: Special issue of ASMBI for y‐BIS 2019: Recent Advances in Business Analytics and Data Science

2021 ◽  
Vol 37 (2) ◽  
pp. 157-158
Author(s):  
Tahir Ekin ◽  
Gavino Puggioni ◽  
Paulo Canas Rodrigues
Keyword(s):  
Data Science ◽  
Business Analytics ◽  
Special Issue ◽  
Recent Advances

Big data analysis on Job Trends using R

2019 ◽  
Vol 12 ◽  
Author(s):  
Somula Ramasubbareddy ◽  
Govinda K ◽  
Ashish Kr. Luhach ◽  
Swetha E
Keyword(s):  
Data Analysis ◽  
Data Science ◽  
Business Analytics ◽  
Job Seekers ◽  
Domain Experts ◽  
Data Analyst ◽  
Use Of Data ◽  
Effective Decision ◽  
R Programming ◽  
Effective Decision Making

Background: Now-a-days, the demand for data science related job positions have seen huge due to the recent data explosion incurred by the industries and organizations globally. The necessity to harness and utilize the amount of information hidden inside these huge datasets for effective decision-making has become the need of the hour. However, this scenario is where a data analyst or a data scientist comes into play. They are domain experts who have the skillset and expertise to extract hidden meaning from data and convert them into useful insights. This work illustrates the use of data mining and advanced data analysis techniques such as data aggregation, summarization along with data visualization using R tool to understand and analyse the job trends in United states of America(USA) and then drill down to analyse job trends for data science related job positions from year 2011 to 2016. Objective: This paper discusses the general job trends in US and how the job seekers are migrating from one place to another place using Visa for different titles, majorly for business analytics. Methods: Analytics is done using R programming, different functions of the programming on various parameters and inference is drawn on the result. Results: The aim of this analysis is to predict the job trends in line with demand, region, employers, wages in USD.

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