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Instigation and Development of Data Science
Published in Pallavi Vijay Chavan, Parikshit N Mahalle, Ramchandra Mangrulkar, Idongesit Williams, Data Science, 2022
Priyali Sakhare, Pallavi Vijay Chavan, Pournima Kulkarni, Ashwini Sarode
Firstly, we need to check whether there is access for the data to the company. Then, we have to check the quality of the data that is available in the company. Many companies have the habit of keeping the key data, so cleaning of data can be already done. Mainly, the data can be stored in data warehouses, data marts, databases, etc. Data warehouse is a system where it combines the data from different sources into a central repository to store the data and support data mining, machine learning, and business intelligence. Data mart is a subset of a data warehouse where it focuses on a specific area which only allows the authorized user to quickly access critical data without wasting time over finding through an entire data warehouse. A database is used to store the data.
Business Intelligence, Big Data and Data Governance
Published in Pedro Novo Melo, Carolina Machado, Business Intelligence and Analytics in Small and Medium Enterprises, 2019
Hélder Quintela, Davide Carneiro, Luís Ferreira
Summarizing, BI contributes positively to several key aspects of organizational success: It facilitates the generation of knowledge about the organization and its domain, allowing the organization to devise solutions that better tackle current challenges and prevent future ones or at least put the organization in a better position to face them.Its continued use at several levels allows the organization to continuously improve as a whole, as each decision maker understands increasingly better the organization and the challenges it faces. In a sense, it can be stated that it allows the organization to collectively learn how to perform better.By providing more and valuable information about the organization and its challenges, BI also allows for richer decision environments, supporting creative problem-solving, and allowing the organization to device new solutions, products, or services that allow it to adapt quicker to changes in its environment.
Conventional and Unconventional Data Mining for Better Decision-Making
Published in Seweryn Spalek, Data Analytics in Project Management, 2018
As we have seen, wrong data, bad data, or too much data are common causes of decisions, and often our collection of data and the interpretation are influenced by our biases. To counter this we need to ensure that we collect the proper amount of data, process the data, and analyze it in the best way possible. It is this quest to find patterns and knowledge that is at the core of data mining. Although data mining will have varying definitions, we will define it broadly to encompass aspects of domains such as business intelligence, big data, data analytics, statistical analysis, and machine learning, but where there is a specific goal to be achieved. Data mining helps us make informed assumptions about facts we do not know at the present.
Preventing Reverse Engineering of Critical Industrial Data with DIOD
Published in Nuclear Technology, 2023
Arvind Sundaram, Hany S. Abdel-Khalik, Mohammad G. Abdo
Business intelligence (BI) is a strategic initiative aimed at incorporating data analytics with business information.1,2 The goal of BI is to provide a comprehensive and concise interpretation of vast amounts of data collected from systems and their users to maximize shareholder value. One of the primary components of BI is the subset focusing on statistics, optimization, and prediction, also known as business analytics.3 Such services are often performed through third-party vendors that specialize in the development and application of artificial intelligence and machine learning (AI/ML) techniques to process and interpret the massive amounts of data collected, colloquially known as “big data.” In the nuclear community, there is a growing need to incorporate AI/ML tools to perform predictive maintenance,4 detect loss-of-coolant accidents,5 detect malicious cyberattacks,6 and enhance the safety and operational efficiency of reactors.7
Factors influencing business intelligence adoption: evidence from Jordan
Published in Journal of Decision Systems, 2022
Zaid Jaradat, Ahmed Al-Dmour, Hashem Alshurafat, Huthaifa Al-Hazaima, Mohannad Obeid Al Shbail
To improve the decision-making process within organisations, Shariat and Hightower (Shariat & Hightower, 2007) suggest the adoption of BI as a category of applications that provides useful information for management decision making. With BI adoption, an organisation could ultimately improve performance through informed decision-making (Vinekar et al., 2009). According to Niu et al. (Niu et al., 2021), BI is able to store various types of data and then convert them into actable information which the organisation can utilise in making informed decisions and improve the efficiency and productivity of their business. Equally, BI can be perceived as the potential of organisation in effectively utilising the information attained from their normal business undertakings (Vidal-García et al., 2019). Furthermore, BI plays a key role in optimising the effectiveness of business as it provides information on fresh prospects, potential risks, and additional business insights, leading to improved decision-making process (Vinekar et al., 2009). The advantages of BI include fast and dependable reporting, superior market choice, enhanced customer services, increased revenues (Rikhardsson & Yigitbasioglu, 2018), superior knowledge processing, in addition to reduce cost and decision time (Rouhani et al., 2016).
The challenges and practice of metal industries into global supply chain integration: A literature review
Published in Cogent Engineering, 2020
Alie Wube Dametew, Birehanu Beshah, Frank Ebinger
Besides, Kasi (2005) found that the SCOR model is strong on the technical dimensions but it is weak and not emphasis on the social dimensions of supply chain firms. On the other side, the performance dashboard is a performance dashboard is a dynamic management tool that is used by an organization to gauge performance and progress toward specific goals is a tool for organizing and providing ready access to performance information (Key et al., 2008). This provides to bring together key performance metrics of an organization or an individual on one display. The dashboard is often used in business intelligence or executive information systems to allow easy monitoring of key performance indicators. Since function as an organization magnifying glass, as a result of measuring, monitoring, and managing the business process. Meanwhile, form this performance analysis section, the author found that, the evaluation and assessment of supply chain firm performance were done in different contexts and scenarios. Temporarily according to this result from the numerous evaluation strategy or systems some are: performance measures employed based on strategic (Azfara et al., 2014; Xu et al., 2007), operational or tactical focus (Beamon, 1999; Gunasekaran et al., 2004) levels. Since, this strategic, operational or tactical performance evaluation and measurement provides to enhance organizational productivity and firm profitability (Gunasekaran et al., 2004).