Building an Analytics Culture to Boost a Data-Driven Entrepreneur's Business Model

This chapter treats the movement that marks, affects, and transforms any part of business and society. It is about big data that is creating, and the value generating that companies, startups, and entrepreneurs have to derive through sophisticated methods and advanced tools. This chapter suggests that analytics can be of crucial importance for business and entrepreneurial practices if correctly aligned with business process needs and can also lead to significant improvement of their performance and quality of the decisions they make. So, the main purpose of this chapter are exploring why small business, entrepreneur, and startups have to use data analytics and how they can integrate, operationally, analytics methods to extract value and create new opportunities.

Remote Patient Monitoring for Healthcare

Remote patient monitoring involves the collection of data from wearable sensors that typically requires analysis in real time. The real-time analysis of data streaming continuously to a server challenges data mining algorithms that have mostly been developed for static data residing in central repositories. Remote patient monitoring also generates huge data sets that present storage and management problems. Although virtual records of every health event throughout an individual's lifespan known as the electronic health record are rapidly emerging, few electronic records accommodate data from continuous remote patient monitoring. These factors combine to make data analytics with continuous patient data very challenging. In this chapter, benefits for data analytics inherent in the use of standards for clinical concepts for remote patient monitoring is presented. The openEHR standard that describes the way in which concepts are used in clinical practice is well suited to be adopted as the standard required to record meta-data about remote monitoring. The claim is advanced that this is likely to facilitate meaningful real time analyses with big remote patient monitoring data. The point is made by drawing on a case study involving the transmission of patient vital sign data collected from wearable sensors in an Indian hospital.

Proactive Information Security Strategy for a Secure Business Environment

Taking into consideration the competitive market, the protection of information infrastructure for a company means competitive advantage. The protected information along with risk analysis are the underlying decision making in the company: either development, positioning on new markets, expansion on emerging markets, exit markets, or acquisitions. At the same time, the protection of information together with operational business intelligence systems are the keys for the decisions of CEOs. Implementing appropriate security measures to counter threats such as attacks can be blocked, or its effects can be mitigated. In this context, this chapter intends to be a thorough reflection on the awareness of potential threats and vulnerabilities, as well as a preoccupation towards cooperation in countering them with well-established rules and mechanisms created at a national and organizational level. The results are relevant to better understand how the actors involved in information and communication technologies could develop new models of information systems and risk management strategies.

Intelligent Big Data Analytics

Intelligent big data analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores intelligent big data analytics from a managerial perspective. More specifically, it first looks at the age of trinity and argues that intelligent big data analytics is at the center of the age of trinity. This chapter then proposes a managerial framework of intelligent big data analytics, which consists of intelligent big data analytics as a science, technology, system, service, and management for improving business decision making. Then it examines intelligent big data analytics for management taking into account four managerial functions: planning, organizing, leading, and controlling. The proposed approach in this chapter might facilitate the research and development of intelligent big data analytics, big data analytics, business intelligence, artificial intelligence, and data science.

The Impact of Creating a Business Intelligence Platform on Higher Education

In today's ever-changing global environment, the higher education industry is facing many diversified and evolving challenges and its landscape is becoming more competitive, dynamic, and complex. To proactively operate in such a changing and complicated environment, innovation, creativity, information, and knowledge represent key competitive edges that need to be introduced, cultivated, and managed effectively. The American University in Cairo (AUC) is a leading institution of higher education in the Middle East North Africa (MENA) region that recognized early on the power of knowledge and the need for a paradigm shift in management that capitalizes on innovative information and communication technologies. Accordingly, the university embarked on an ambitious journey as the first higher education institution in Egypt to build a state-of-the-art business intelligence (BI) platform that would support proactive, informed decision-making as a distinctive and sustainable competitive advantage.

Credit Rating Forecasting Using Machine Learning Techniques

Credit ratings are an important metric for business managers and a contributor to economic growth. Forecasting such ratings might be a suitable application of big data analytics. As machine learning is one of the foundations of intelligent big data analytics, this chapter presents a comparative analysis of traditional statistical models and popular machine learning models for the prediction of Moody's long-term corporate debt ratings. Machine learning techniques such as artificial neural networks, support vector machines, and random forests generally outperformed their traditional counterparts in terms of both overall accuracy and the Kappa statistic. The parametric models may be hindered by missing variables and restrictive assumptions about the underlying distributions in the data. This chapter reveals the relative effectiveness of non-parametric big data analytics to model a complex process that frequently arises in business, specifically determining credit ratings.

The Strategic Adoption of Big Data in Organizations

This chapter investigates the strategic adoption of big data (BD) and analytics (BDA) in organizations. BD represents a large and complex phenomenon which spans different disciplines. BD research is fraught with many challenges. This research develops BD adoption model that could aid organizations in assessing the strategic importance of BD to gain different advantages including gaining a competitive advantage. BD is considered a radical technology and realizing its advantages in organizations is challenged with many factors. The research attempts to outline the different aspects of BD highlighting different contributions, implications and recommendations.

Census Data Analysis and Visualization Using R Tool

As a result of increased usage of internet, a huge amount of data is collected from variety of sources like surveys, census, and sensors in internet of things. This resultant data is coined as big data and analysis of this leads to major decision making. Since the collected data is in raw form, it is difficult to understand inherent properties and it becomes just a liability if not analyzed, summarized, and visualized. Although text can be used to articulate the relation between facts and to explain the findings, presenting it in the form of tables and graphs conveys information effectively. Presentation of data using tools to create visual images in order to gain more insights into data is called as data visualization. Data analysis is processing and interpretation of data to discover useful information and to deduce certain inferences based on the values. This chapter concerns usage of R tool and understanding its effectiveness for data analysis and intelligent data visualization by experimenting on data set obtained from University of California Irvine Machine Learning Repository.

Optimizing and Enhancing Digital Marketing Techniques in Intellectual Big Data Analytics

The authors in this chapter show the essence, dignity, current state, and development prospects of avatar-based management using blockchain technology for improving implementation of economic solutions in the digital economy of Russia. The purpose of this chapter is not to review the existing published work on avatar-based models for policy advice, but to try an assessment of the merits and problems of avatar-based models as a solid basis for economic policy advice that is mainly based on the work and experience within the recently finished projects Triple H Avatar, an avatar-based software platform for HHH University, Sydney, Australia. The agenda of this project was to develop an avatar-based closed model with strong empirical grounding and micro-foundations that provides a uniform platform to address issues in different areas of digital economic and creating new tools to improve blockchain technology using the intelligent visualization techniques for big data analytic.

Using Intelligent Agents Paradigm in Big Data Security Risks Mitigation

Big data has a great potential in improving the efficiency of most of the specific information society instruments. Yet, because it uses the newly introduced cloud technology support, it may need continuous improvements especially in the security assurance area. In this chapter, a possible solution based on the intelligent agent paradigm in securing the big data infrastructure is presented. This approach will also require some changes at the general strategy level. The main accent is on using big data techniques and tools to ensure data security. Unfortunately, due to some security-related issues at the global level, the business environment must increase the amount of resources driven to this area.