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Data analytics may be heavily reliant on technology such as statistical models, machine learning algorithms, big data, and cloud computing; however, its outcome depends largely on human qualities such as experience, intuition, value, and judgement. Human knowledge is at the core of data analytics and knowledge management plays a key role in the ana...
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Context 1
... is to know why; it sits at the pinnacle of human understanding. Wisdom is the most powerful and critical type of knowledge that drives human endeavors as reflected in the "Start with Why" Golden Circle model by Sinek (2011) where the why drives the how to achieve the what as illustrated in figure 1. ...
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... data analytics process is like climbing the DIKW pyramid, and can be summarized in three major phases. Each phase corresponds to one of three dimensions (technology, people, and organization), and represents one of three philosophical paradigms (positivism, constructivism, and pragmatism) as shown in Figure 1. ...
Context 3
... is to know why; it sits at the pinnacle of human understanding. Wisdom is the most powerful and critical type of knowledge that drives human endeavors as reflected in the "Start with Why" Golden Circle model by Sinek (2011) where the why drives the how to achieve the what as illustrated in figure 1. ...
Context 4
... data analytics process is like climbing the DIKW pyramid, and can be summarized in three major phases. Each phase corresponds to one of three dimensions (technology, people, and organization), and represents one of three philosophical paradigms (positivism, constructivism, and pragmatism) as shown in Figure 1. ...
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Citations
... Manfaat utama dari data analytics ada empat dalam audit internal, yaitu untuk meningkatkan efisiensi, mempercepat identifikasi pola/tren/hubungan, meningkatkan "internal audit coverage", serta mengembangkan strategi peran auditor internal (Raghava, 2017). Sementara itu, dalam konteks knowledge management, data analytics dapat bermanfaat untuk peningkatan value secara hirarkikal, yaitu; dari data menjadi informasi, dari informasi menjadi knowledge, dan dari knowledge menjadi wisdom (Wang, 2018). ...
... Teknik statistik yang digunakan berupa statistik deskriptif, korelasi, decition tree, dan text analytics. Jika ditinjau dari teori integrasi data dengan knowledge management (Wang, 2018), maka hasil statistic deskriptif mampu mengubah data menjadi informasi. Data peserta pelatihan dapat dideskripsikan menjadi informasi berupa 75% peserta merupakan generasi millennials. ...
... Rule DT tersebut mengungkap bahwa beberapa variasi kesenjangan digital mempunyai dampak pada kelas keyakinan peserta terhadap penerapan data analytics dalam audit. Pohon keputusan keyakinan peserta terhadap penerapan data analytics dapat diprediksi dengan kondisi sebagai berikut: kategori generasi Y&Z, tapi masih yunior (masa kerja kurang dari 10 tahun) dan paham statistik&/TIK Hasil decision tree ini memperkuat bukti implementasi "knowledge creation" (Wang, 2018). Informasi korelasi (beberapa variable kesenjangan digital dengan keyakinan penggunaan data analytics) dapat menjadi knowledge. ...
Pandemi COVID-19 membawa perubahan di beberapa bidang termasuk penyelenggaraan pelatihan. Untuk mencegah penyebaran COVID-19, penyelenggaraan pelatihan banyak dialihkan ke dalam bentuk nonklasikal. Hal ini ditempuh sebagai alternatif agar pengembangan kompetensi tetap berjalan sembari tetap mengupayakan keselamatan jiwa peserta pelatihan. Namun apakah Widyaiswara sebagai tenaga pengajar dalam pelatihan memiliki kompetensi yang cukup dalam penguasaan teknologi khususnya aplikasi yang digunakan dalam kegiatan pembelajaran sehingga berdampak pada capaian kompetensi peserta pelatihan. Penelitian ini bertujuan menganalisis hubungan tingkat penguasaan teknologi oleh Widyaiswara dengan capaian kompetensi peserta pelatihan saat pandemi COVID-19. Metode yang digunakan pada penelitian ini menggunakan pendekatan kuantitatif dengan data primer berupa hasil pengukuran tingkat penguasaan teknologi pada pembelajaran daring oleh Widyaiswara dan hasil capaian kompetensi peserta Pelatihan sebelum dan pada saat pandemi. Hasil dari penelitian didapati bahwa tingkat penguasaan teknologi dalam pembelajaran daring berada pada tingkat memuaskan sedangkan hasil capaian kompetensi peserta sebelum dan saat pandemi juga mengalami kenaikan. Sebagai kesimpulan dapat dikatakan bahwa Widyaiswara telah memiliki kompetensi penguasaan teknologi dalam pembelajaran daring yang berdampak pada hasil capaian kompetensi peserta pelatihan di masa pandemi.
... Fase kedua berupa fase kreasi 'knowledge' atau fase peningkatan penggunaan experiential knowledge. Sedangkan fase ketiga berupa fase penerapan 'knowledge' atau fase peningkatan penggunaan collective knowledge (Wang, 2018). Data banyak digunakan organisasi untuk pengambilan keputusan dalam upaya pencapaian tujuannya (Hidayatul, 2016). ...
The development of technology and the current fast-paced conditions require Widyaiswara to have
digital literacy skills, especially in the use of learning methods and media. However, there are still Widyaiswara
who are technologically stuttering and have not been able to maximize the use of technology for educating,
training, and teaching activities as well as the function and role of Widyaiswara. In addition, the inclusion of the
millennial generation in the world of bureaucracy requires up-to-date learning methods and media so that the
material presented can be more interesting. This article aims to measure the ability of Widyaiswara in digital
literacy in the implementation of training using indicators set by the Ministry of Education and Culture. The
method used in this research is descriptive analysis method with data collection techniques through distributing
questionnaires to Widyaiswara, literature studies, and observations in the field through monitoring and
evaluation of training. The results show that Widyaiswara have high digital literacy skills, but still need to increase
Widyaiswara's participation in non-classical training, besides that it is also necessary to increase the variety and
number of digital reading materials, and the need for Widyaiswara's involvement in the digital community.
... Many different terms have been used to describe the process of identifying patterns and gaining insights from raw data to support problem solving (Sircar 2009;Wang 2018). According to Davenport & Harris (2007, p.7), the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and factbased management to drive decisions and actions , is called data analytics. ...
... According to Davenport & Harris (2007, p.7), the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and factbased management to drive decisions and actions , is called data analytics. According to Wang (2018) data analytics is a process of increasing understanding of reality, starting from the observations of a phenomenon to reaching the pinnacle of wisdom, empowering informed decisions and practical actions. ...
During the past two decades the implementation and adoption of information technology has rapidly increased. As a consequence the way businesses operate has changed dramatically. For example, the amount of data has grown exponentially. Companies are looking for ways to use this data to add value to their business. This has implications for the manner in which (financial) governance needs to be organized. The main purpose of this study is to obtain insight in the changing role of controllers in order to add value to the business by means of data analytics. To answer the research question a literature study was performed to establish a theoretical foundation concerning data analytics and its potential use. Second, nineteen interviews were conducted with controllers, data scientists and academics in the financial domain. Thirdly, a focus group with experts was organized in which additional data were gathered. Based on the literature study and the participants responses it is clear that the challenge of the data explosion consist of converting data into information, knowledge and meaningful insights to support decision-making processes. Performing data analyses enables the controller to support rational decision making to complement the intuitive decision making by (senior) management. In this way, the controller has the opportunity to be in the lead of the information provision within an organization. However, controllers need to have more advanced data science and statistic competences to be able to provide management with effective analysis. Specifically, we found that an important skill regarding statistics is the visualization and communication of statistical analysis. This is needed for controllers in order to grow in their role as business partner.
... From an epistemological perspective, DIKW represents the increasing level of human understanding through the incremental process of discovering, creating, and applying human knowledge, and helps to better understand human decision-making. Wang (2018) proposed a conceptual data analytics process model using the wisdom pyramid as the overarching structure. The model described data analytics as a three-phase process as shown in Figure 1. ...
... The A2E model aligns with KM in that EI represents the tacit knowledge embodied in people, whereas AI represents the explicit knowledge processed by technology. Tacit knowledge is 'a knowledge that we cannot tell' (Polanyi, 1966, p. 5), while explicit knowledge 'can be codified or described using languages and other conceptual means' (Wang, 2018). Nonaka and Takeuchi (1995, p. 36) contracted tacit and explicit knowledge as 'knowledge of experience (body)' vs. 'knowledge of rationality (mind).' ...
Decision Support Systems have significance, as today firms turn to big data, machine learning, and artificial intelligence to guide strategy development and improve organizational performance. However, technology is not enough; human intelligence is necessary. This paper introduces Artificial Intelligence to the Emotional Intelligence Model, which blends technology and humanity to support strategic decision-making. Such a model builds on the Data-Information-Knowledge-Wisdom hierarchy and knowledge management to integrate five types of intelligence. The consumer electronics retail giant Best Buy is used as a case to illustrate the relevance of the model. The presented framework provides a powerful, mental model to support organizational strategists and business executives.
... These could be internal, explicit or tacit knowledge. 8 The active screening of external knowledge is often not directly associated with knowledge management, but rather with the term regulatory intelligence. 9 ...
The efficient handling of information and resources is key for achieving success within a commercial organisation. However, From the two enablers in the ICH Q10 guidelines – risk and knowledge management – knowledge management plays a secondary role. In contrast to risk management, according to ICH Q9, there is no clear guidance about what a structured knowledge management process should look like. The article discusses five things you can implement right now to improve your company’s knowledge management directly without first creating a formal knowledge management environment.
Renewable energy projects are at the crux of all Chinese-funded investment in sub-Saharan Africa, which accounts for some 56% of all Chinese-led investments globally. However, the prevailing problem is that about 568 million people were still without electricity access in 2019 across urban and rural areas in sub-Saharan Africa, which does not commensurate with the United Nations Sustainable Development Goal (SDG7) of ensuring affordable and clean energy for all. Previous studies have assessed and improved the efficiency of integrated power generation systems often combined on three levels, power plant, solar panel, and fuel cells, and integrated into national grids or off-grid systems for a sustainable supply of power. This study has included a lithium-ion storage system as a key component in a hybridized renewable energy generation system for the first time that has proven to be efficient and investment worthy. The study also examines the operational parameters of Chinese-funded power plant projects in sub-Saharan Africa and their effectiveness in achieving SDG-7. The novelty of this study is evident in the proposed integrated multi-level hybrid technology model of solid oxide fuel cells, temperature point sensors, and lithium batteries powered by a solar system and embedded in thermal power plants as an alternative electrical energy system for domestic and industrial use in sub-Saharan Africa. Performance analysis of the proposed power generation model indicates its complementary capacity of generating additional energy output with thermodynamics energy and exergy efficiencies of 88.2% and 67.0% respectively. The outcome of this study draws the attention of Chinese investors, governments in sub-Saharan African countries, and top industry players to the following: to consider refocusing their energy sector policy initiatives and strategies towards exploring the lithium resource base in Africa, optimizing energy generation cost, recouping optimal profit from their renewable energy technology investments, and making electricity supply clean, sustainable, and affordable for use in sub-Saharan Africa.
In the Cyber world today managing threats dynamically, is challenging, moreover generation of knowledge and enhancing knowledge management (KM) capabilities is becoming crucial due to the dynamics of technological advancements. In this context a regulatory mechanism is essential; this resilience required is achieved through data analytics which bridges the gaps between the challenges faced in cyber space and implementable realistic solutions. Along-with the technological advancements it becomes imperative to optimally utilize and align knowledge management capabilities. A need was foreseen to reconsider KM capabilities in the fields of computer security, data management, also legal and risk management. The researchers have attempted to work on the aspect of sustainability, in handling challenges and solutions in implementing effective cyber security and in building better KM infrastructures; through innovative enabler such as Data analytics. In the proposed effort to elaborate this review study, assessment and quantitative analysis is recommended. Introduction In today's highly competitive world, IT infrastructures are preferred to be equipped with Cyber security mechanisms to curtail down the cyber threats. Protecting sensitive data, computer systems, networks and software applications from cyber attacks generates a large amount of data which can be analyzed substantially to form information security resources for better knowledge management around cyber security. Such protecting mechanisms are used by individuals and enterprises to deal with the challenges such as tampering and/or unauthorized access to vital resources and other computerized systems. Every organization has these important resources which are called as intellectual assets that include hardware, software, and data. With the continuous increase in the number of cyber threats and its effects on the organization due to the complexity of the cyber attacks; organizations are struggling to protect the information in an upcoming highly dynamic business environment. It has become essential and important to secure the intellectual assets including digital processes, information and IT systems from tampering systems and data stored within, exploitation of resources via attacks. These intellectual assets should be legally protected to achieve security of confidential information of an organization such as source code, solution manual, executable, live databases of clients, passwords and other confidential information stored on servers, financial data, and employee details etc.
Data analytics is a key to unlock the untapped power of knowledge hidden in the trenches of big data in the age of information and intelligence. However, not all analytics efforts can achieve the desired outcomes and impacts. A successfully executed data analytics project relies on the application of an effective process model that facilitates multidisciplinary collaborations and balance technical efficiency with organizational effectiveness. This article introduces an integrated process model for data science and machine learning including its theoretical foundation and step-by-step descriptions and guidelines. The goal of this article is to provide concise, easy-to-follow guidance for data professionals and domain experts to apply this novel process model in their day-to-day collaborative and iterative analytics effort.
Knowledge management is a consolidation of various endeavours and disciplines. This chapter assesses the space of knowledge management and examines the significance of running a successful business with an efficient management system. To have a smooth management in a company, all the employees in the company need to access all the required information, which may be comprised of documents, collaboration of teams, policies in various departments, etc. All of these require an efficient knowledge management system. A framework for characterising the various tools and techniques available to knowledge management practitioners are well explored in the chapter.
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.
