Leveraging predictive analytics for strategic decision-making: Enhancing business performance through data-driven insights

World Journal of Advanced Research and Reviews, Год журнала: 2024, Номер 22(3), С. 1927 - 1934

Опубликована: Июнь 30, 2024

This paper explores the transformative role of predictive analytics in enhancing strategic decision-making and business performance. It delves into components analytics, including data mining, machine learning, statistical techniques. highlights its historical evolution technological enablers like big platforms, cloud computing, AI. The examines how improves profitability, efficiency, market share by providing actionable insights from raw data. also discusses emerging trends such as advancements AI, Internet Things (IoT), real-time while addressing associated risks privacy ethical considerations. conclusion underscores necessity adopting for sustainable growth competitive advantage today's data-driven environment.

Язык: Английский

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Strategic financial decision-making in sustainable energy investments: Leveraging big data for maximum impact

International Journal of Management & Entrepreneurship Research, Год журнала: 2024, Номер 6(6), С. 1982 - 1996

Опубликована: Июнь 24, 2024

In the context of escalating environmental concerns and transition towards a greener economy, sustainable energy investments have emerged as pivotal area for financial growth innovation. This paper outlines strategic framework decision-making in investments, emphasizing transformative role big data. By integrating data analytics into investment process, stakeholders can enhance market analysis, risk assessment, performance monitoring, predictive modeling, leading to more informed effective strategies. The delves various sources, analytical tools, technologies that facilitate collection, processing, interpretation vast amounts information. Additionally, it presents case studies illustrating successful applications solar wind projects, highlighting best practices common challenges. discussion extends future trends, including advancements artificial intelligence machine learning, which are poised further revolutionize sector. concludes with recommendations developing data-driven approach, building robust infrastructures, fostering culture continuous learning adaptation. leveraging data, investors maximize impact their drive growth, contribute global transition. Keywords: Sustainable Energy Investments, Big Data Analytics, Strategic Financial Decision-Making, Market Analysis, Risk Assessment, Predictive Modeling.

Язык: Английский

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Driving energy transition through financial innovation: The critical role of Big Data and ESG metrics

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(6), С. 1434 - 1452

Опубликована: Июнь 14, 2024

Driving the transition to sustainable energy is a critical global imperative, and financial innovation plays pivotal role in accelerating this process. This paper examines intersection of innovation, big data, Environmental, Social, Governance (ESG) metrics advancing transition. By harnessing power data integrating ESG considerations into investment decisions, institutions can drive meaningful change towards more future. The begins by exploring concept transition, highlighting its importance, drivers, challenges. It then delves discussing examples opportunities it presents for driving Subsequently, significance understanding consumption patterns optimizing efficiency, along with influencing decisions corporate behavior. emphasized, focus on their synergistic potential investments informing decision-making processes. Case studies are presented illustrate successful applications sector. Finally, discusses challenges future directions, including regulatory considerations, technological advancements, collaboration. concludes underscoring importance continued calls collective action Keywords: Energy Transition, Financial Innovation, Big Data, Metrics, Sustainability, Investment Decisions, Sustainable Energy, Renewable Climate Change

Язык: Английский

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Frameworks for effective data governance: best practices, challenges, and implementation strategies across industries

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(7), С. 1666 - 1679

Опубликована: Июль 25, 2024

This paper explores frameworks for effective data governance, emphasizing the importance of robust policies, processes, roles, and metrics. It outlines best practices ensuring high quality, privacy, security while highlighting stakeholder engagement role technology. The also discusses implementation challenges, including organizational, technical, regulatory, cultural obstacles. presents tailored strategies various industries such as financial services, healthcare, retail, manufacturing, public sector. Future directions research include integration AI machine learning, evolving privacy regulations, challenges posed by big IoT. Effective governance is crucial managing risks, compliance, unlocking full potential assets across industries. Keywords: Data Governance, Quality Management, Privacy, Regulatory Compliance.

Язык: Английский

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Enhancing data quality through comprehensive governance: Methodologies, tools, and continuous improvement techniques

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(7), С. 1680 - 1694

Опубликована: Июль 25, 2024

In the era of data-driven decision-making, ensuring data quality is paramount for organizations seeking to leverage their assets effectively. This paper explores comprehensive strategies enhancing through robust governance, methodologies, tools, and continuous improvement techniques. It highlights critical dimensions quality, including accuracy, completeness, consistency, timeliness, validity, uniqueness. discusses various assessment techniques, such as profiling, auditing, metrics. The also examines role cleansing, enrichment, integration, interoperability in maintaining high quality. Additionally, it provides an overview leading management evaluation criteria, best practices implementation. Finally, underscores importance monitoring, feedback loops, root cause analysis, fostering organization's culture. By adopting these strategies, can ensure reliability integrity data, improved business outcomes. Keywords: Data Quality, Governance, Profiling, Cleansing, Continuous Improvement.

Язык: Английский

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Leveraging Large Language Models for Enhancing Safety in Maritime Operations

Applied Sciences, Год журнала: 2025, Номер 15(3), С. 1666 - 1666

Опубликована: Фев. 6, 2025

Maritime operations play a critical role in global trade but face persistent safety challenges due to human error, environmental factors, and operational complexities. This review explores the transformative potential of Large Language Models (LLMs) enhancing maritime through improved communication, decision-making, compliance. Specific applications include multilingual communication for international crews, automated reporting, interactive training, real-time risk assessment. While LLMs offer innovative solutions, such as data privacy, integration, ethical considerations must be addressed. concludes with actionable recommendations insights leveraging build safer more resilient systems.

Язык: Английский

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Comprehensive review of metal complexes and nanocomposites: Synthesis, characterization, and multifaceted biological applications

Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(6), С. 1935 - 1951

Опубликована: Июнь 13, 2024

This review paper provides an extensive analysis of the synthesis, characterization, and multifaceted biological applications metal complexes nanocomposites derived from a diverse array biopolymeric ligands. These ligands, including chitosan, 2-hydroxybenzaldehyde, 4-aminopyridine imine, among others, have shown remarkable potential due to their biocompatibility, biodegradability, functional versatility. The delves into various synthetic strategies, conventional green synthesis approaches, highlights advanced characterization techniques such as spectroscopy, microscopy, thermal analysis, X-ray diffraction. Emphasizing broad spectrum activities exhibited by these compounds, covers antimicrobial, anticancer, antioxidant, enzyme inhibition, drug delivery applications. By synthesizing current research identifying key challenges future directions, this aims provide valuable insights for researchers in medicinal chemistry, materials science, biotechnology, related fields. Keywords: Metal Complexes, Nanocomposites, Synthesis, Characterization, Biological Application.

Язык: Английский

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Advancements and obstacles in improving the energy efficiency of maritime vessels: A systematic review

Marine Pollution Bulletin, Год журнала: 2025, Номер 214, С. 117688 - 117688

Опубликована: Фев. 22, 2025

The maritime industry, a cornerstone of global trade, faces mounting pressure to improve energy efficiency and minimize environmental impact. To address this, systematic review is proposed analyze trends advancements, aiming the ships. This comprehensively examines contemporary methodologies persistent challenges in assessing ship efficiency. We recent advancements design operational practices that promote gains. Additionally, we explore evolution regulatory frameworks industry standards governing assessment. Key challenges, including data availability, measurement accuracy, technological limitations, are scrutinized along with potential solutions. aims equip researchers, practitioners, policymakers comprehensive understanding current landscape, paving way for future research policy initiatives drive sustainable transportation.

Язык: Английский

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Engineering solutions for clean energy: Optimizing renewable energy systems with advanced data analytics

Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(6), С. 2050 - 2064

Опубликована: Июнь 13, 2024

This paper explores the role of advanced data analytics in optimizing renewable energy systems to achieve clean objectives. As world transitions towards sustainable sources, intermittency and variability sources present significant challenges. Traditional approaches managing these challenges often fall short terms efficiency scalability. However, offers promising solutions by leveraging large volumes optimize production, storage, distribution. discusses various techniques such as predictive modeling, optimization algorithms, grid management strategies enabled analytics. Case studies highlight real-world applications wind solar optimization, showcasing effectiveness data-driven improving output integration. Despite potential benefits, privacy, security, regulatory frameworks remain important considerations. Looking ahead, integration IoT sensor technologies holds promise for further enhancing performance systems. By fostering collaboration between researchers, policymakers, industry stakeholders, we can accelerate adoption propel transition a future. Keywords: Renewable Energy, Advanced Data Analytics, Predictive Modeling, Optimization Algorithms, Grid Integration, Sustainability.

Язык: Английский

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Optimizing Maritime Energy Efficiency: A Machine Learning Approach Using Deep Reinforcement Learning for EEXI and CII Compliance

Sustainability, Год журнала: 2024, Номер 16(23), С. 10534 - 10534

Опубликована: Ноя. 30, 2024

The International Maritime Organization (IMO) has set stringent regulations to reduce the carbon footprint of maritime transport, using metrics such as Energy Efficiency Existing Ship Index (EEXI) and Carbon Intensity Indicator (CII) track progress. This study introduces a novel approach deep reinforcement learning (DRL) optimize energy efficiency across five types vessels: cruise ships, car carriers, oil tankers, bulk container under six different operational scenarios, varying cargo loads weather conditions. Traditional fuels, like marine gas (MGO) intermediate fuel (IFO), challenge compliance with these standards unless engine power restrictions are applied. combines DRL alternative fuels—bio-LNG hydrogen—to address challenges. algorithm, which dynamically adjusts parameters, demonstrated substantial improvements in optimizing consumption performance. Results revealed that while DRL, increased by up 10%, EEXI values decreased 8% 15%, CII ratings improved 10% 30% scenarios. Specifically, heavy loads, DRL-optimized system achieved 7.2 nmi/ton compared 6.5 traditional methods reduced value from 4.2 3.86. Additionally, consistently outperformed optimization methods, demonstrating superior lower emissions all tested highlights potential advancing suggests further research could explore applications other vessel integrating additional machine techniques enhance optimization.

Язык: Английский

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