scholarly journals The Effect of Knowledge Management Systems on Measuring Success Indicators for Saudi Arabia 2030

2019 ◽  
Vol 10 (4) ◽  
pp. 31
Author(s):  
Bader A. Alyoubi
Keyword(s):  
Saudi Arabia ◽  
Big Data ◽  
Middle East ◽  
Data Analytics ◽  
Social Impact ◽  
Big Data Analytics ◽  
Strategic Objectives ◽  
Success Indicators ◽  
Vision 2030 ◽  
Common Platform

Vision 2030 is designed to place the Kingdom of Saudi Arabia (KSA) as a trading and financial hub in the Middle East. Ninety-six strategic objectives are framed for Vision 2010. Whilst these objectives are very inspiring, challenges are seen in integrating them under a single unifying framework. Unless the diverse objectives are integrated, knowledge and learning of team members are brought on a common platform to measure the success indicators, achieving the vision would be difficult. Objective of the paper is to develop a KM model that will help to measure the success indicators of Vision 2030. A literature review helped to understand the barriers, processes, and methodology of KM frameworks. The findings indicate that Vision 2030 is wide in scope with 96 loosely connected strategic objectives. An overarching framework that links all these objectives and places them on a common platform is not evident. These inputs were used to design the KM Vision 2030 model that links all the objectives and helps to gather metrics from the objectives, and measure the success of the project. Some of the metrics that can be considered are linking objectives, milestone achievement, adhering to schedule and budget, economic and social impact on people and businesses, progress in positioning KSA as the leader of Middle East, and others. Some of these measures are qualitative, whilst others are quantitative, implying that a multimodal data collection and analysis method is needed. The model suggests institution of Knowledge Champions, Communities of Practice, big data analytics, knowledge assets development and sharing, and brings all the objectives on a transparent and usable platform. A pilot study in the form of a semi-structured interview and survey was administered to five experts in the field of KM and IT systems. Their findings indicate that big data analytics can play a major role in decision-making and in measuring the project success. The findings also speak of the need to connect the strategic objectives. Recommendations are made to refine the model.

scholarly journals Big Data Analytics: Towards a Model to Understand Development Equity for Villages in Indonesia

2018 ◽  
Vol 164 ◽  
pp. 01004
Author(s):  
Annas Vijaya ◽  
Linda Salma Angreani ◽  
Mokhamad Amin Hariyadi
Keyword(s):  
Developing Countries ◽  
Big Data ◽  
Information Systems ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Monitoring And Evaluation ◽  
Prototype Model ◽  
Strategic Objectives ◽  
Public Monitoring

The aim of this paper is to design a prototype model that can be used to better understand development equity for villages in terms of public monitoring and evaluation. In designing the model, the research has reviewed several techniques of big data analytics as well as alignment of business strategic objectives and technology. The prototype model also tested using several types of data. Although some obstacles have found, as it also found in the reviewed literature, a prototype model which can guide researchers and practitioners to understand ways to capture public monitoring is presented in this paper. Furthermore, Information systems researchers could use this prototype model for further research to get a deeper understanding of big data analytics roles for development, particularly in developing countries.

scholarly journals Sehaa: A Big Data Analytics Tool for Healthcare Symptoms and Diseases Detection Using Twitter, Apache Spark, and Machine Learning

2020 ◽  
Vol 10 (4) ◽  
pp. 1398 ◽  
Author(s):  
Shoayee Alotaibi ◽  
Rashid Mehmood ◽  
Iyad Katib ◽  
Omer Rana ◽  
Aiiad Albeshri
Keyword(s):  
Saudi Arabia ◽  
Big Data ◽  
Data Analytics ◽  
Smart Cities ◽  
Heart Diseases ◽  
Big Data Analytics ◽  
Extraction Methods ◽  
Apache Spark ◽  
Kingdom Of Saudi Arabia ◽  
Multiple Feature

Smartness, which underpins smart cities and societies, is defined by our ability to engage with our environments, analyze them, and make decisions, all in a timely manner. Healthcare is the prime candidate needing the transformative capability of this smartness. Social media could enable a ubiquitous and continuous engagement between healthcare stakeholders, leading to better public health. Current works are limited in their scope, functionality, and scalability. This paper proposes Sehaa, a big data analytics tool for healthcare in the Kingdom of Saudi Arabia (KSA) using Twitter data in Arabic. Sehaa uses Naive Bayes, Logistic Regression, and multiple feature extraction methods to detect various diseases in the KSA. Sehaa found that the top five diseases in Saudi Arabia in terms of the actual afflicted cases are dermal diseases, heart diseases, hypertension, cancer, and diabetes. Riyadh and Jeddah need to do more in creating awareness about the top diseases. Taif is the healthiest city in the KSA in terms of the detected diseases and awareness activities. Sehaa is developed over Apache Spark allowing true scalability. The dataset used comprises 18.9 million tweets collected from November 2018 to September 2019. The results are evaluated using well-known numerical criteria (Accuracy and F1-Score) and are validated against externally available statistics.

scholarly journals Big Data Analytics Strategy Framework: A Case of Crowd Management During the Hajj Pilgrimage, Mecca, Saudi Arabia

2021 ◽  
Vol 14 (4) ◽  
pp. 1975-1984
Author(s):  
Hanaa Ali Aldahawi
Keyword(s):  
Saudi Arabia ◽  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics ◽  
Crowd Management ◽  
Data Framework ◽  
Crowd Control ◽  
Adoption And Implementation ◽  
Big Data Applications ◽  
Paper Review

The objective of the present study was an investigation of applications of big data analytics in Hajj and Umrah for pilgrims, who come to Saudi Arabia every year for tourism and observation of religious rites as per the sacred beliefs of Islam. It has now become a necessity to see more applications of big data analytics in these pilgrimages because of the growing number of people every year. Therefore, crowd control, crowd management and conflict management are essential for reduction of stress, troubles, fatalities, accidents, theft and possible deaths during Hajj and Umrah events. Developing a predictive data analytic model for Hajj and Umrah will improve the efficiency, gross domestic product (GDP), surveillance, revenue generation, opportunities and satisfaction for the pilgrimages. In this paper, review of big data tools was presented along with their use in the decision support system and how it can be used for surveillance and crowd management. A robust big data framework applicable for Hajj and Umrah events was also presented in this paper. This was meant to aid seamless adoption and implementation of big data applications across sectors and government parastatals involved in Hajj and Umrah. The presented framework was also included all the relevant use cases related to these pilgrimages.

Big Data Analytics: The Next Big Thing

2019 ◽  
Vol 54 (5) ◽  
pp. 20
Author(s):  
Dheeraj Kumar Pradhan
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

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

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.

A Review on Big Data Analytics Tools in Context with Scalability

2019 ◽  
Vol 7 (2) ◽  
pp. 273-277
Author(s):  
Ajay Kumar Bharti ◽  
Neha Verma ◽  
Deepak Kumar Verma
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics

Big Data Analytics Solutions and Challenges

2017 ◽  
Vol 49 (004) ◽  
pp. 825--830
Author(s):  
A. AHMED ◽  
R.U. AMIN ◽  
M. R. ANJUM ◽  
I. ULLAH ◽  
I. S. BAJWA
Keyword(s):  
Big Data ◽  
Data Analytics ◽  
Big Data Analytics
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