scholarly journals ASSESSING THE DIGITAL MATURITY OF AN ENTERPRISE AS THE FIRST STEP TO DIGITAL TRANSFORMATION

2021 ◽  
Vol 9 (12) ◽  
pp. 369-370
Author(s):  
O. A. Aydel
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Success Factors ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Highly Qualified ◽  
Qualified Personnel ◽  
It Support

The questions of assessing an enterprise’s digital maturity as the first step in digital transformation are considered. Particular attention is paid to such success factors of digital transformation as awareness of the need for change, availability of quality IT-support and competencies in this area, as well as highly qualified personnel in the field of big data analytics and availability of a strategy of comprehensive digital transformation for the enterprise. 

scholarly journals A Preliminary Systematic Performanceon Critical Success Factors Categories for Big Data Analytics

2019 ◽  
Vol 9 (1) ◽  
pp. 2320-2324 ◽  
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Critical Success Factors ◽  
Success Factors ◽  
Research Question ◽  
Big Data Analytics ◽  
Data Driven ◽  
Successful Implementation ◽  
Critical Success ◽  
Data Driven Decisions

Big Data could be used in any industry to make effective data-driven decisions. The successful implementation of Big Data projects requires a combination of innovative technological, organizational, and processing approaches. Over the last decade, the research on Critical Success Factors (CSFs) within Big Data has developed rapidly but the number of available publications is still at a low level. Developing an understandingof the Critical Success Factors (CSFs) and their categoriesare essential to support management in making effective data-driven decisions which could increase their returns on investments.There islimited research conducted on the Critical Success Factors (CSFs) of Big DataAnalytics (BDA) development and implementation.This paper aims to provide more understanding about the availableCritical Success Factors (CSFs) categoriesfor Big Data Analytics implementation and answer the research question (RQ) “What are the existing categories of Critical Success Factors for Big Data Analytics”.Based on a preliminary Systematic Literature Review (SLR) for the available publications related to Big Data CSFs and their categories in the last twelve years (2007-2019),this paper identifiesfive categoriesfor Big Data AnalyticsCritical Success Factors(CSFs), namelyOrganization, People, Technology, Data Management, and Governance categories.

scholarly journals Artificial intelligence and machine learning: changing paradigm in diagnostics and imaging

2019 ◽  
Vol 8 (1) ◽  
pp. 382
Author(s):  
Rahul Badwaik
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Healthcare Setting ◽  
Digital Transformation ◽  
Current Status ◽  
Healthcare Industry ◽  
Review Of The Literature

Healthcare industry is currently undergoing a digital transformation, and Artificial Intelligence (AI) is the latest buzzword in the healthcare domain. The accuracy and efficiency of AI-based decisions are already been heard across countries. Moreover, the increasing availability of electronic clinical data can be combined with big data analytics to harness the power of AI applications in healthcare. Like other countries, the Indian healthcare industry has also witnessed the growth of AI-based applications. A review of the literature for data on AI and machine learning was conducted. In this article, we discuss AI, the need for AI in healthcare, and its current status. An overview of AI in the Indian healthcare setting has also been discussed.

Much- needed business digital transformation through big data, internet of things and blockchain capabilities: implications for strategic performance in telecommunication sector

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Anam Bhatti ◽  
Haider Malik ◽  
Ahtisham Zahid Kamal ◽  
Alamzeb Aamir ◽  
Lamya Abdulrahman Alaali ◽  
...  
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Data Quality ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Digital Transformation ◽  
Equation Modeling ◽  
Content Type ◽  
Strategic Performance ◽  
Dependent Variables

PurposeIn the field of business, digital transformation is the integration of digital technology into all areas of business, from generating to deliver value to customers. This concept is essential for sustainable growth of a company and its overall economy. Based on this fact, this authentic and informative research is conducted whose major aim is to examine the importance of digital transformation within a business through big data, the Internet of things and blockchain-based capabilities for overall strategic performance within the telecom sector in China.Design/methodology/approachFor that aim, data quality and technology competence are considered as independent variables, strategic performance as dependent variable and big data analytics capabilities, Internet of things capabilities and blockchain capabilities routinization acted as mediators within this paper. In its data collection mechanism, an online survey was conducted in which questionnaires are randomly distributed to the telecom sector's professionals in which only 343 of them gave their valid outcomes. After collecting primary data, confirmatory factor analysis (CFA) and structural equation modeling (SEM)–based statistical outcomes have been generated.FindingsResults indicate that there is a significant relationship between data quality and strategic performance and between technological competence and strategic performance. Also, the big data analytics and Internet of Things capabilities acted as significant mediating role between both independent and dependent variables. But blockchain capabilities routinization is that variable that acts as an insignificant mediator between independent and dependent variables' relationship.Originality/valueOverall, this study is an informative and attractive source for the Chinese government, its telecom industry, administrative body and related ones to understand the importance of such IT capabilities' implications within their operating activities for their strategic performance management. Also, related field scholars can utilize its reliable data in their research analysis. Its major limitations are (1) lack of qualitative/ mixed method of research and (2) lack of comparative analysis that may impact the acceptability factor of this paper, and this weakness can be overcome by upcoming scholars in their research.

scholarly journals Significance of Technology and Digital Transformation in Shaping the Future of Oil and Gas Industry

2021 ◽  
Vol 12 (3) ◽  
pp. 3345-3352
Author(s):  
Shubham Parsoya Et.al
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Internet Of Things ◽  
Data Analytics ◽  
Oil And Gas ◽  
Big Data Analytics ◽  
Oil And Gas Industry ◽  
Digital Transformation ◽  
Gas Industry ◽  
The Future

Digital transformation in the field of oil and Gas industry is already a significant impact creator. It is actually act like catalyst through which the overall functionality of the oil and gas industry get enhanced and the overall output with the help of technologically-advanced mechanism, increased up to manifold. In the present scenario, the over-all quest is not just about the volume of the oil and petroleum, but it is also regarding the overall value generated throughout the process. And such enhanced level of value generation is taking place with great pace with the help of enhanced level of implementations of different types of technologies in different type of activities related to the oil and gas industry. In the present scenario, oil and gas industry’s business model is no longer depending upon just the inflated and narrow based value-chain mechanism. It is actually depending upon the almost all modernized and futuristic technologies. The modern technologies include big data analytics, 3D printing technology, cyber security, digital marketing, Artificial Intelligence, Internet of Things, drone technologies, database management system, etc. all these technologies are not only supports in handling the overall business capability of the oil and Gas Industries, but also eliminate the overall negative impact generating elements. With the help of technologies and digital transformation, the overall profitability of the oil and gas industry enhanced. Digital transformation is a prominent and significant impact creator which is not limited to the oil and gas industry, but also reaching up to the all-global level Businesses. It is transforming the overall business operations by enhancing the speed of innovation and making the use of practical knowledge base which ultimately enhance the overall power of operations and increase efficiencies. With the emergence of digital transformation technologies especially with the emergence of big data analytics, the Internet of Things and Artificial Intelligence have supports several types of innovative and new ways of developing and transforming the overall market as well as the customer satisfaction in significant manner. All such innovative technologies and digital transformations are contributing significantly in shaping the future of oil and gas industry

The Strengths, Weaknesses, Opportunities, and Threats Analysis of Big Data Analytics in Healthcare

2022 ◽  
pp. 1703-1718
Author(s):  
Chaojie Wang
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Success Factors ◽  
Swot Analysis ◽  
Big Data Analytics ◽  
Clear Understanding ◽  
Healthcare Organizations ◽  
Effective Use ◽  
The Cost

Improving the performance and reducing the cost of healthcare have been a great concern and a huge challenge for healthcare organizations and governments at every level in the US. Measures taken have included laws, regulations, policies, and initiatives that aim to improve quality of care, reduce costs of care, and increase access to care. Central to these measures is the meaningful and effective use of Big Data analytics. To reap the benefits of big data analytics and align expectations with results, researchers, practitioners, and policymakers must have a clear understanding of the unique circumstances of healthcare including the strengths, weaknesses, opportunities, and threats (SWOT) associated with the use of this emerging technology. Through descriptive SWOT analysis, this article helps healthcare stakeholders gain awareness of both success factors and issues, pitfalls, and barriers in the adoption of big data analytics in healthcare.

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