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Journal articles on the topic 'Azure Health Data Services'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Praveen, Borra. "Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions." International Journal of Recent Technology and Engineering (IJRTE) 13, no. 2 (2024): 21–26. https://doi.org/10.35940/ijrte.B8111.13020724.

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<strong>Abstract:</strong> Azure IoT, developed by Microsoft, is a leading platform in the realm of Internet of Things (IoT), revolutionizing industries through enhanced connectivity, robust data management, and advanced analytics. This paper provides an in-depth exploration of Azure IoT's foundational technologies such as Azure IoT Hub and Azure Sphere, pivotal for ensuring secure device communication and comprehensive IoT security. Azure IoT Hub facilitates secure bidirectional communication between IoT devices and the cloud, supporting scalability to millions of devices across diverse secto

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Borra, Praveen. "Impact and Innovations of Azure IoT: Current Applications, Services, and Future Directions." International Journal of Recent Technology and Engineering (IJRTE) 13, no. 2 (2024): 21–26. http://dx.doi.org/10.35940/ijrte.b8111.13020724.

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Azure IoT, developed by Microsoft, is a leading platform in the realm of Internet of Things (IoT), revolutionizing industries through enhanced connectivity, robust data management, and advanced analytics. This paper provides an in-depth exploration of Azure IoT's foundational technologies such as Azure IoT Hub and Azure Sphere, pivotal for ensuring secure device communication and comprehensive IoT security. Azure IoT Hub facilitates secure bidirectional communication between IoT devices and the cloud, supporting scalability to millions of devices across diverse sectors. In manufacturing, it em

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Dheerendra, Yaganti. "Designing Privacy-First Health Monitoring Architectures Using Federated AI and FHIR-Compliant Azure Health Data Services In .NET." Journal of Scientific and Engineering Research 11, no. 8 (2024): 215–20. https://doi.org/10.5281/zenodo.15241066.

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The rapid advancement of digital health technologies necessitates architectures that ensure data privacy, regulatory compliance, and intelligent analytics. This paper presents a privacy-first health monitoring system that integrates Federated Artificial Intelligence (AI), Fast Healthcare Interoperability Resources (FHIR), and Azure Health Data Services within a .NET framework. The proposed architecture enables real-time health data collection and decentralized machine learning while preserving patient privacy and meeting HIPAA and FHIR compliance standards. By leveraging federated learning, th

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Venkata, Tadi. "Evaluating Advanced Azure Monitoring and Alerting Strategies in Diverse Large-Scale Enterprise Environments." Journal of Scientific and Engineering Research 9, no. 9 (2022): 94–107. https://doi.org/10.5281/zenodo.13338082.

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This study evaluates the performance and scalability of advanced monitoring and alerting strategies for data-intensive applications deployed on Microsoft Azure within diverse, large-scale enterprise environments. Leveraging key Azure services such as Azure Functions, Azure Data Factory (ADF) Pipelines, Kusto, Azure Service Bus, and Event Grid, the research aims to bridge the gap between theoretical best practices and real-world applications. By conducting a comprehensive analysis across various industry sectors, the study identifies the practical challenges, solutions, and adaptations necessar

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Ravi Kiran Pagidi, Jaswanth Alahari, Aravind Ayyagiri, Prof.(Dr) Punit Goel, Prof.(Dr.) Arpit Jain, and Er. Aman Shrivastav. "Best Practices for Implementing Continuous Streaming with Azure Databricks." Universal Research Reports 8, no. 4 (2021): 268–92. http://dx.doi.org/10.36676/urr.v8.i4.1428.

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Continuous data streaming is essential for modern applications that require real-time processing of large data sets. Azure Databricks, a scalable data analytics platform, is widely used to implement such streaming systems. This paper presents best practices for implementing continuous streaming with Azure Databricks, focusing on key aspects such as architecture design, data ingestion, and stream processing optimization. The integration of Apache Spark within Databricks enables efficient, fault-tolerant stream processing at scale, making it ideal for handling high-throughput data streams. Key c

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Eliwa, Entesar Hamed I., Amr Mohamed El Koshiry, Tarek Abd El-Hafeez, and Ahmed Omar. "Secure and Transparent Lung and Colon Cancer Classification Using Blockchain and Microsoft Azure." Advances in Respiratory Medicine 92, no. 5 (2024): 395–420. http://dx.doi.org/10.3390/arm92050037.

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Background: The global healthcare system faces challenges in diagnosing and managing lung and colon cancers, which are significant health burdens. Traditional diagnostic methods are inefficient and prone to errors, while data privacy and security concerns persist. Objective: This study aims to develop a secure and transparent framework for remote consultation and classification of lung and colon cancer, leveraging blockchain technology and Microsoft Azure cloud services. Dataset and Features: The framework utilizes the LC25000 dataset, containing 25,000 histopathological images, for training a

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Urvangkumar, Kothari. "The Revolutionizing Dairy Industry Analytics through Real-Time Data Engineering." International Journal of Innovative Research in Engineering & Multidisciplinary Physical Sciences 8, no. 3 (2020): 1–8. https://doi.org/10.5281/zenodo.14945246.

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The dairy industry is experiencing substantial changes because of powerful real-time data engineering and cloud computing technologies. Dairy enterprises employ SQL and NoSQL databases together with Microsoft Azure services as well as Power BI and Microsoft BI tools which help improve efficiency and optimize production and maintain regulatory compliance. This paper examines data engineering functions across predictive maintenance operations while analyzing livestock health surveillance alongside supply chain management and quality control systems. The research investigates the influence of AI-

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Moret-Tatay, Carmen, Hernán Mario Radawski, and Cecilia Guariglia. "Health Professionals’ Experience Using an Azure Voice-Bot to Examine Cognitive Impairment (WAY2AGE)." Healthcare 10, no. 5 (2022): 783. http://dx.doi.org/10.3390/healthcare10050783.

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Virtual Assistants (VA) are a new groundbreaking tool for screening cognitive impairment by healthcare professionals. By providing the volume of data needed in healthcare guidance, better treatment monitoring and optimization of costs are expected. One of the first steps in the development of these items is the experience of the healthcare professionals in their use. The general goal of the current project, WAY2AGE, is to examine healthcare professionals’ experience in using an Azure voice-bot for screening cognitive impairment. In this way, back-end services, such as the ChatBot, Speech Servi

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Holilah, Holilah, Husyen Ali Alhabsy, Tb Muhammad Farhan Adnan, et al. "Aplikasi Kebugaran Defense In Depth Untuk Aplikasi Kebugaran Perusahaan Start-Up Menggunakan Microsoft Azure." Jurnal Ilmiah Sains dan Teknologi 9, no. 1 (2025): 10–19. https://doi.org/10.47080/saintek.v9i1.3867.

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A start-up company in the fitness and health sector has developed an innovative virtual training platform. The platform allows users to take live fitness classes via their computer, tablet or smartphone, leveraging artificial intelligence (AI) and high-quality video streaming for an interactive and personalized training experience. The platform consists of three main components: the frontend layer (web and mobile applications), the backend layer (application servers), and the data storage layer (cloud database). As the popularity of these platforms increases, companies face challenges in manag

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Wagholikar, Kavishwar B., Shreekanth V. Joshi, Vishal V. Pai Vernekar, et al. "Cloud Services for Patient Cohort Identification Using the Informatics for Integrating Biology and the Bedside Platform." BioMed Research International 2020 (July 8, 2020): 1–8. http://dx.doi.org/10.1155/2020/2851713.

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Despite the widespread use of the “Informatics for Integrating Biology and the Bedside” (i2b2) platform, there are substantial challenges for loading electronic health records (EHR) into i2b2 and for querying i2b2. We have previously presented a simplified framework for semantic abstraction of EHR records into i2b2. Building on our previous work, we have created a proof-of-concept implementation of cloud services on an i2b2 data store for cohort identification. Specifically, we have implemented a graphical user interface (GUI) that declares the key components for data import, transformation, a

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Park, Hyun Sang, Kwang Il Kim, Ho-Young Chung, et al. "A Worker-Centered Personal Health Record App for Workplace Health Promotion Using National Health Care Data Sets: Design and Development Study." JMIR Medical Informatics 9, no. 8 (2021): e29184. http://dx.doi.org/10.2196/29184.

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Background Personal health record (PHR) technology can be used to support workplace health promotion, and prevent social and economic losses related to workers’ health management. PHR services can not only ensure interoperability, security, privacy, and data quality, but also consider the user’s perspective in their design. Objective Using Fast Healthcare Interoperability Resources (FHIR) and national health care data sets, this study aimed to design and develop an app for providing worker-centered, interconnected PHR services. Methods This study considered the user’s perspective, using the hu

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Gómez Fernández, Juan F., Eduardo Candón Fernández, and Adolfo Crespo Márquez. "A Structured Data Model for Asset Health Index Integration in Digital Twins of Energy Converters." Energies 18, no. 12 (2025): 3148. https://doi.org/10.3390/en18123148.

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A persistent challenge in digital asset management is the lack of standardized models for integrating health assessment—such as the Asset Health Index (AHI)—into Digital Twins, limiting their extended implementation beyond individual projects. Asset managers in the energy sector face challenges of digitalization such as digital environment selection, employed digital modules (absence of an architecture guide) and their interconnection, sources of data, and how to automate the assessment and provide the results in a friendly decision support system. Thus, for energy systems, the integration of

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Mushtaque Temrekar, Ms Misba. "A Comparative Analysis of Global Data Privacy Regulations and Their Implementation by Major Cloud Service Providers." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 05 (2025): 1–9. https://doi.org/10.55041/ijsrem46907.

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Abstract As businesses continue to adopt cloud computing for their digital operations, the importance of data privacy and regulatory compliance has become increasingly pronounced. While cloud platforms offer scalable solutions for storage, processing, and service delivery, their global presence introduces challenges in adhering to complex legal requirements. This paper explores how three leading cloud service providers—Amazon Web Services (AWS), Microsoft Azure, and Google Cloud—implement and navigate key data protection regulations, including the European Union’s General Data Protection Regul

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Achar, Sandesh. "Requirement of Cloud Analytics and Distributed Cloud Computing: An Initial Overview." International Journal of Reciprocal Symmetry and Theoretical Physics 2 (2015): 12–18. http://dx.doi.org/10.18034/ijrsps.v2.70.

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A better and more streamlined user experience is the result of the research demonstrating how cloud analytics tools and software are particularly effective for processing vast data sets, producing insights in easily digestible formats on demand, and improving the user interface. Cloud computing is a large-scale information technology solution that can customize and deliver a new kind of environment based on information technology to everyday users, in particular to IT and computing systems users. Cloud computing was developed by Amazon Web Services (AWS) and Microsoft Azure. The use of cloud c

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Timberlake, Kathryn, Alicia Koo, Michelle Science, et al. "Tracking and Reporting Antimicrobial Use: Development of an Antimicrobial Stewardship Dashboard." Journal of the Pediatric Infectious Diseases Society 13, Supplement_3 (2024): S22. https://doi.org/10.1093/jpids/piae088.042.

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Abstract Corresponding author: Kathryn Timberlake, 555 University Ave, Toronto, ON M5G1X8, 416-813-6475, Kathryn.timberlake@sickkids.ca No conflicts of interest. Background Tracking and reporting antimicrobial use (AU) is a core element of the Centers for Disease Control and Prevention recommendations for Antimicrobial Stewardship Programs (ASP). Antimicrobial consumption measured in standardized units such as days of therapy (DOT) per 1000 patient days is a common metric used to identify areas for improvement and assess the impact of antimicrobial stewardship. Additionally, benchmarking betwe

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Aishat, Abdullahi, Sanni Ajoge Naseer, Abubakar Yusuf, and Auwal Ahmed Mohammed. "The Design of an Intelligent Healthcare Chatbot for Managing Ante-Natal Recommendations." International Journal of Innovative Science and Research Technology 7, no. 6 (2022): 1829–34. https://doi.org/10.5281/zenodo.6979180.

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Chatbot is an Artificial Intelligent technology (AI) that has been used in several computer assistive social interactions. They are designed to convincingly simulate how humans behave in a natural conversation with a partner. Information Technology and AI have been deployed in health care especially in medical information but such deployment can be enhanced with a chatbot in antenatal services. Maternal and newborn mortality is still on the rise in Nigeria and medical personnel are in short supply, hence a virtual expert that can assist the pregnant mothers in basic medical advice is suitable.

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Donovitz, Gary S. "Low complication rates of testosterone and estradiol implants for androgen and estrogen replacement therapy in over 1 million procedures." Therapeutic Advances in Endocrinology and Metabolism 12 (January 2021): 204201882110152. http://dx.doi.org/10.1177/20420188211015238.

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Background: Testosterone (T) deficiency (TD) in men and women and estrogen (E) deficiency (ED) in women increasingly affects the overall health and quality of life of patients. T implants have seen increased utilization over the past decade. We evaluated continuation rates and adverse events that occurred during T therapy by reviewing practitioner reported data on compressed human-identical T implants for the treatment of TD in both men and women collected over 7 years. Methods: This was a retrospective review of data collected prospectively from men and women from 2012 and 2019. Men who had t

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Krishna Kishor Tirupati, Rahul Arulkumaran, Nishit Agarwal, Anshika Aggarwal, and Prof.(Dr) Punit Goel. "Integrating Azure Services for Real Time Data Analytics and Big Data Processing." Darpan International Research Analysis 12, no. 1 (2024): 207–32. http://dx.doi.org/10.36676/dira.v12.i1.112.

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Integrating Azure services for real-time data analytics and big data processing is a transformative approach that leverages the power of cloud computing to handle vast amounts of data at scale. Azure offers a wide array of services such as Azure Synapse Analytics, Azure Data Lake, Azure Stream Analytics, and Azure Databricks, which together enable businesses to extract valuable insights from both structured and unstructured data in real time. These services provide seamless integration, allowing for real-time data ingestion, transformation, and analysis, facilitating quicker decision-making pr

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Nedosnovanyi, O. Y., O. I. Cherniak, and V. V. Golinko. "COMPARATIVE ANALYSIS OF CLOUD SERVICES FOR GEOINFORMATION DATA PROCESSING." Information technology and computer engineering 57, no. 2 (2023): 50–57. http://dx.doi.org/10.31649/1999-9941-2023-57-2-50-57.

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The article is devoted to a comparative analysis of cloud services for processing geographic data. It describes in detail the services - Google Cloud, Amazon Web Services and Microsoft Azure - that provide tools for storing, processing and analyzing large amounts of geographic data. The article also describes the parameters of geoinformation services, the access algorithm, and examples of program code for processing satellite data. The article describes such opportunities and limitations of using cloud services as automation, security and scalability. The conclusions and recommendations for fu

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Holkuziev, Diyorjon. "Infrastructure Automation in Cloud Environments Using Terraform." Universal Library of Engineering Technology 02, no. 03 (2025): 06–11. https://doi.org/10.70315/uloap.ulete.2025.0203002.

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The article examines the principles and practices of automating the deployment and management of cloud infrastructure using Terraform. The relevance of this study is determined by the rapid increase in complexity of cloud environments and the risk of numerous incidents arising from manual configurations. Misconfigurations have become one of the leading causes of outages and data breaches. Accordingly, automating resource provisioning and management becomes a critical task to ensure reproducibility, security, and accelerated time-to-market. The objective of this work is to conduct a comprehensi

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Sigala, Ndansi Seraphin. "Microservices Architecture in Cloud Computing: A Software Engineering Perspective on Design, Deployment, and Management." International Journal of Research and Innovation in Social Science IX, no. XV (2025): 215–39. https://doi.org/10.47772/ijriss.2025.915ec0013.

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In modern software engineering, it has gained much attention as an effective paradigm to traditional monolithic architectures. Microservices provide an application development approach in a module-based way, where larger systems are divided into a number of small, independently deployable, and loosely coupled services. It performs pre-defined functions, with loose coupling among these services via APIs, which interact with other services; thus, modifications or failures in one will not bring down the whole application. This architecture thus gives faster development cycles, continuous delivery

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Shira, Bala Mohammed, Jibrin Dauda, and Ahmed Mohammed. "Unavailability of Antenatal Care Facilities as a Factor Affecting Accessibility to Antenatal Care Services among Pregnant Women in Internally Displaced Persons’ Camps in Borno State, Nigeria." INTERNATIONAL JOURNAL OF MEDICAL EVALUATION AND PHYSICAL REPORT 7, no. 3 (2023): 64–71. http://dx.doi.org/10.56201/ijmepr.v7.no3.2023.pg64.71.

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The study examined availability of antenatal care facilities as a factor affecting accessibility to antenatal care services among pregnant women in Internally Displaced Persons’ (IDPs) Camps in Borno State, Nigeria. Survey type of descriptive research design was adopted and the population of the study comprised pregnant women in fifteen (15) IDPs’ Camps in Maiduguri Municipal, Borno State totaling four thousand four hundred and forty (N=4,440). Simple random sampling technique was used and selected 400 respondents from six (6) selected IDPs’ Camps. The research instrument was a researcher deve

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Traverso, Alberto, Simone Barbieri, Marco Denti, Antonio Esposito, and Carlo Tacchetti. "Abstract A052: The S-RACE Platform: Empowering Healthcare Real-World Data with Artificial Intelligence (AI) Using a Cloud-Based Approach." Clinical Cancer Research 31, no. 13_Supplement (2025): A052. https://doi.org/10.1158/1557-3265.aimachine-a052.

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Abstract Prognostic and predictive clinical decision support systems based on Real-World Evidence (RWE) data are crucial in clinical research. These systems help clinicians optimize therapeutic choices, reduce adverse events, and enhance personalized medicine. AI plays a key role in these advancements, as machine learning algorithms uncover hidden patterns beyond human capability, leading to novel clinical insights. However, the clinical translation of such algorithms depends heavily on data quality. RWE data are often unstructured, sparse, and poorly curated, requiring extensive manual proces

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Ravi Kiran Pagidi, Pramod Kumar Voola, Amit Mangal, Aayush Jain, Prof.(Dr) Punit Goel, and Dr S P Singh. "Leveraging Azure Data Lake for Efficient Data Processing in Telematics." Universal Research Reports 9, no. 4 (2022): 643–74. http://dx.doi.org/10.36676/urr.v9.i4.1397.

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In the telematics industry, the continuous generation of large volumes of data presents significant challenges in terms of storage, processing, and analysis. Azure Data Lake, a scalable and secure data storage solution, offers an efficient platform to handle these massive datasets. This paper explores the application of Azure Data Lake in telematics for efficient data processing, focusing on its capacity to store vast amounts of structured and unstructured data while providing seamless integration with various analytics tools. By leveraging Azure Data Lake, organizations can enhance their data

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Parag, Bhardwaj. "Designing Multi-Tier Applications Using Azure App Services." International Journal on Science and Technology 11, no. 1 (2020): 1–13. https://doi.org/10.5281/zenodo.14613886.

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Building and deploying cloud based applications with Azure App Services provides a robust and scalable option for designing multi-tier applications. Azure App Services is a fully managed platform that makes it easier for developers to create, deploy, and host web apps, mobile backbends, and RESTful APIs—with minimal infrastructure management. With Azure’s integrated tools and services, this abstract will explore how to benefit and methodology for designing multi-tier applications. Once again, in a typical multi-tier architecture, the application is separated into different layers l

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Minar, Phillip, Abigail Samuels, Tomoyuki Mizuno, et al. "BIOLOGIC PRECISION DOSING IS NOW AVAILABLE AT THE BEDSIDE FOR CHILDREN AND ADULTS WITH INFLAMMATORY BOWEL DISEASE RECEIVING INFLIXIMAB." Inflammatory Bowel Diseases 28, Supplement_1 (2022): S98—S99. http://dx.doi.org/10.1093/ibd/izac015.160.

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Abstract INTRODUCTION There is significant variability in infliximab (IFX) pharmacokinetics (PK) in children and adults with multiple population PK models developed and several covariates identified to better predict drug clearance. Fortunately, therapeutic drug monitoring (TDM) is widely available and can be used to simplify model-informed precision dosing. However, empiric (“trial and error”) dose intensifications following TDM to achieve targeted levels can delay obtaining an optimal drug exposure and is a risk for super-therapeutic levels. In this study, we highlight the formal processes t

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Suraj, Khot, and Mali Abhijeet. "Implementation of MQTT Protocol for Artificial Intelligence." International Journal of Engineering and Management Research 14, no. 3 (2024): 21–27. https://doi.org/10.5281/zenodo.11467295.

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The IoT-Based Attendance Management System is a sophisticated solution leveraging Azure services and MQTT protocol for efficient attendance tracking. The system comprises a Face Device equipped with facial recognition capabilities, which captures attendance data and communicates with Azure IoT Hub. The Azure IoT Hub, acting as the central hub, receives and processes attendance data from the face device, utilizing MQTT for real-time communication. A dedicated MQTT service, facilitated by the MOSQUITTO BROKER, subscribes to the Azure IoT Hub, ensuring seamless data flow between the face device a

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Vijaya Sekhar Godavarti. "Azure Fabric: Microsoft's Unified Data Platform for the Enterprise." International Journal of Scientific Research in Computer Science, Engineering and Information Technology 11, no. 1 (2025): 2333–40. https://doi.org/10.32628/cseit251112245.

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This article examines Microsoft's Azure Fabric, a revolutionary cloud-scale service transforming enterprise data management through unified storage and interface capabilities. It explores how Azure Fabric addresses the challenges of managing distributed data systems in modern enterprises by providing a comprehensive solution that integrates various data services into a single platform. The article encompasses the evolution of Microsoft's data platform, highlighting the transition from specialized solutions to a unified approach. It analyzes Azure Fabric's key features, including its unified st

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Shi, Jiong, Liping Jin, and Jun Li. "The Integration of Azure Sphere and Azure Cloud Services for Internet of Things." Applied Sciences 9, no. 13 (2019): 2746. http://dx.doi.org/10.3390/app9132746.

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Internet of Things (IoT) has become one of the key factors that enables, drives and accelerates the digital transformation all over the world. The vision of the IoT is not only the immediate access to the data but also the ability to turning data into intelligence. As such, there is a growing number of public cloud computing providers offering IoT related services, including data processing, data analyzing and data visualization. However, with tens of billions of microcontroller-powered devices getting involved in the era of IoT, the concerns for overall security, privacy and cost are rising c

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Oladimeji, Olawumi. "Enhancing Data Pipeline Efficiency Using Cloud-Based Big Data Technologies: A Comparative Analysis of AWS and Microsoft Azure." Journal of Multidisciplinary Research and Innovation 2, no. 1 (2024): 11–22. http://dx.doi.org/10.70560/n43nvk83.

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This study conducts a comprehensive comparative analysis of data pipeline efficiency between Amazon Web Services (AWS) Glue and Microsoft Azure Data Factory, two leading cloud-based big data technologies. As organizations increasingly rely on data-driven decision-making, optimizing data pipeline performance is crucial for processing large volumes of information from diverse sources. The research evaluates AWS Glue and Azure Data Factory based on key metrics such as processing speed, scalability, cost efficiency, and fault tolerance, using synthetic datasets ranging from 10GB to 500GB. The resu

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Borra, Praveen. "An overview of cloud data warehouses: Amazon Redshift (AWS), Azure Synapse (Azure), and Google BigQuery (GCP)." international journal of advanced research in computer science 15, no. 3 (2024): 23–27. http://dx.doi.org/10.26483/ijarcs.v15i3.7099.

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Massive volumes of structured and semi-structured data originating from various sources can be efficiently stored, managed, and analysed using a data warehouse. It is specifically designed for query and analysis purposes, rather than for transaction processing, offering a strong foundation for making data-driven decisions. Organizations and businesses are drawn to cloud platforms for numerous reasons, including faster development and deployment, superior performance, low latency, and cost efficiency. The study delves into the cloud data warehouse services provided by three prominent cloud serv

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Upendra, Chauhan, Singh Ramkrishna, Kaur Ramandeep, Singh Shubham, Kumari Tanisha, and Chauhan Ankur. "Covid-19 Prediction using Azure Data Factory (ADF)." Covid-19 Prediction using Azure Data Factory (ADF) 8, no. 11 (2023): 9. https://doi.org/10.5281/zenodo.10213496.

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Developing an advanced COVID-19 screening scheme using Azure's heterogeneous datasets coupled with ECDC data. Combining comprehensive datasets, including medical records, radiological imaging scan, clinical details, and epidemiological information from ECDC will produce a refined and accurate model for diagnosing COVID-19 and integrating the capabilities of data lakes and data warehouses. Azure's dataset integration incorporates information like X- rays, CT scans, patient demographics, clinical symptoms,while ECDC data encompasses broad epidemiological, transmission rates, and geographical spr

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Venkata, Raman Immidisetti. "Azure NetApp Files: The Premier Cloud-Based File Storage Solution for Enterprise Workloads." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 9, no. 2 (2023): 1–7. https://doi.org/10.5281/zenodo.15026957.

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In the evolving landscape of cloud storage, organizations seek high-performance, scalable, and secure file storage solutions that integrate with enterprise workloads. Microsoft Azure offers multiple storage services, including Azure NetApp Files (ANF) and Azure Files. This paper presents a comprehensive analysis of Azure NetApp Files, examining its architecture, performance benchmarks, security features, and enterprise integration capabilities. By comparing ANF with Azure Files and Azure Blob Storage, this study highlights ANF's advantages in handling latency-sensitive, high-throughput workloa

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Naresh, Kumar Rapolu. "Leveraging Machine Learning and Azure AI to Enhance SAP Reporting and Analytics." Journal of Advances in Developmental Research 15, no. 1 (2024): 1–4. https://doi.org/10.5281/zenodo.14979930.

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This research paper has successfully depicted how both machine learning and Azure Artificial Intelligence can be properly leveraged by business entities while enhancing SAP reporting and analytics. By the process of integrating SAP data with the advanced AI capabilities of Microsoft Azure, can obtain predictive analytics along with automation and real-time business insights. This can lead to better operational efficiency and decision-making. Both ML and Azure AI services can include cognitive services, Power BI and machine learning which also can enhance predictive modelling, data processing a

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Sanugommula, Harika. "Azure AKS CRUD Related Issues: Identification, Logging, Resolution, Examples, and Documentation." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 12 (2024): 1–5. https://doi.org/10.55041/ijsrem9545.

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This paper examines the various issues related to Create, Read, Update, and Delete (CRUD) operations in Microsoft Azure services, focusing on the challenges faced during these operations. It details common issues such as data inconsistency, performance bottlenecks, and security vulnerabilities. The paper emphasizes effective strategies for collecting logs and operational details, providing examples of typical scenarios encountered in Azure environments. Furthermore, it outlines resolution techniques for addressing these challenges and highlights the importance of thorough documentation for fut

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Upesh, kumar Rapolu. "Building Scalable Machine Learning Models on Azure for Predictive Analytics in Business Intelligence." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 6, no. 1 (2020): 1–5. https://doi.org/10.5281/zenodo.14752552.

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The following research project has highlighted the implementation of scalable machine learning models on Azure using predictive analytics in the field of business intelligence. It has explored Azure's cloud services to exemplify its data-driven insights. The combination of Azure Machine Learning and Azure Databricks has paved for allowing successful data ingestion followed by optimum model training and deployment. Moreover, this has understood the role of predictive analytics in business intelligence responsible for building scalable machine learning models. The amalgamation of scalability con

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Nandish Shivaprasad. "Enterprise Data Strategy for Azure and SQL Warehousing." Kuwait Journal of Software Design and Development 2, no. 1 (2024): 01–12. https://doi.org/10.52783/kjsdd.259.

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The features outlined in this paper cover several niches that comprise a scalable and secure data architecture design using Azure services and SQL warehousing solutions. It explains how enterprises can derive maximum value from their line of business applications and how BI and analytics can contribute to decision making. It also talks about the use of AI, machine learning and serverless concept in terms of scalability, security and performance. Some opportunities that are also considered in the Azure and SQL warehousing are also looked at as future trends, where real-time processing and impro

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MridulGupta and Sharma Naman. "Comparative Study of Three Translation Services Using APIs." International Journal of Innovative Science and Research Technology 7, no. 5 (2022): 689–90. https://doi.org/10.5281/zenodo.6618376.

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In This paper we Analyze the relationship between the three web services google, aws, azure . In this we take the Data and we translate them using these webservices. The aim of this study to know which webservices translate the data more accurate and error less. The ANOVA test was perform to find the relationship between the webservices .If the value of PR is greater than F then there is a considerable difference between two values are not similar. And if PR is less than F than there is no much difference between two values. In analysis of this experiment we found that PR>F so we can say th

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Krishna Kishor Tirupati, Murali Mohana Krishna Dandu, Vanitha Sivasankaran Balasubramaniam, A Renuka, and Om Goel. "End to End Development and Deployment of Predictive Models Using Azure Synapse Analytics." Innovative Research Thoughts 9, no. 1 (2023): 508–37. http://dx.doi.org/10.36676/irt.v9.i1.1499.

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The end-to-end development and deployment of predictive models using Azure Synapse Analytics represents a comprehensive approach to harnessing advanced analytics for data-driven decision-making. This process integrates various stages of the data science lifecycle within a unified cloud-based environment, leveraging Azure Synapse Analytics' capabilities for data integration, exploration, and model management. Initially, the process involves data ingestion and preparation, where Azure Synapse Analytics facilitates seamless data integration from diverse sources, ensuring that the data is clean, r

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Researcher. "CLOUD COMPUTING FOR EFFICIENT IMPLEMENTATION OF BUSINESS ANALYTICS." International Journal of Computer Engineering and Technology (IJCET) 15, no. 5 (2024): 475–84. https://doi.org/10.5281/zenodo.13845994.

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With exponential growth in data collection of different variety, volatility and with high velocity, we are ending up with huge data. Managing, storing, processing and understanding the hidden details in that data, has become very important for businesses and given rise to the field of business analytics. In cloud computing with the help of cloud services, we can setup resources efficiently, easily and in very less cost. Today, we have 3 large cloud providers Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP). This paper pro- vides a comprehensive comparison of different se

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Nalawade, Prof S. A. "Forecasting Sales Using Azure." International Journal for Research in Applied Science and Engineering Technology 11, no. 1 (2023): 1128–32. http://dx.doi.org/10.22214/ijraset.2023.48749.

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Abstract: The end-to-end business solution is helpful for any business trying to move their data to cloud for further processing, visualizing, monitoring, scaling their business/ business data. Most applications start as small, focused services that solve a single problem and solve it well. But, as a company grows, the needs of its customers multiply. One feature becomes two, which becomes four, then eight and so on. This is manageable, but only to a point. With each additional feature, the complexity of the application infrastructure expands. Figuring out how to properly manage the costs of a

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Muppa, Naveen. "Informatica Intellegent Cloud Services Code Deployment with Azure DevOps." Journal of Artificial Intelligence & Cloud Computing 1, no. 4 (2022): 1–3. http://dx.doi.org/10.47363/jaicc/2022(1)278.

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Continuous Integration/Continuous Delivery (CI/CD) has become a cornerstone of modern software development, enabling teams to deliver high-quality applications at speed and scale. Informatica Intelligent Cloud Services (IICS) provides a robust platform for data integration and management in the cloud. This abstract explores the implementation of CI/CD practices within IICS, focusing on streamlining the development, testing, and deployment of data integration.

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Sharma, Akshay, and Satish Kabade. "Transforming Pension Service Request Processing with Secure, Scalable, and AI-Powered Azure Cloud Technologies." Transforming Pension Service Request Processing with Secure, Scalable, and AI-Powered Azure Cloud Technologies 11, no. 1 (2024): 321–36. https://doi.org/10.32628/IJSRSET2411148.

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Pension service institutions are quickly going digital as they cope with increased service requirements, the demands of regulatory compliance, and challenges posed by cybersecurity. Legacy pension management systems usually have limited scope, are inefficient, and do not provide security on-premise infrastructure (Gartner, 2023). These aspects result in inefficiencies that create delays in processing pensions, an increase in the risk of fraud, and escalated operational costs (Ponemon Institute, 2023). The most critical aspect regarding pension transactions involves the secure, efficient, and s

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Venkata, Raman Immidisetti. "A Comparative Analysis of NetApp Cloud Volumes ONTAP, and Azure NetApp Files: Evaluating Cloud Storage Solutions for Modern Enterprise Needs." International Journal of Leading Research Publication 4, no. 1 (2023): 1–9. https://doi.org/10.5281/zenodo.14880779.

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In cloud-driven digital transformation, organizations are adopting advanced storage solutions to meet demands for scalability, performance, and efficiency. This paper compares two cloud storage platforms: NetApp Cloud Volumes ONTAP (CVO) and Azure NetApp Files (ANF). Both use NetApp's ONTAP technology but differ in deployment models, management frameworks, and cost structures. CVO is a software-defined storage solution extending on-premises ONTAP to multi-cloud environments, supporting workloads like disaster recovery, databases, and file services. ANF, a fully managed Azure-native service, fa

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Bhasker Reddy Ande. "Leveraging Azure OpenAI and Cognitive Services for Enterprise Automation: Streamlining Operations and Enhancing Decision-Making." Journal of Information Systems Engineering and Management 9, no. 4s (2024): 209–16. https://doi.org/10.52783/jisem.v9i4s.11159.

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The integration of Azure OpenAI and Cognitive Services in enterprise automation presents significant opportunities for streamlining operations and enhancing decision-making capabilities. This paper proposes a methodology for combining cloud-based AI technologies to automate routine tasks, improve operational efficiency, and provide real-time insights for data-driven decision-making. We demonstrate how Azure OpenAI's GPT-3 and Cognitive Services such as Text Analytics, Speech-to-Text, and Computer Vision can be leveraged across industries, offering solutions to common business challenges. Exper

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Khanal, Dibya Darshan, and Sushil Maharjan. "Comparative Security and Compliance Analysis of Serverless Computing Platforms: AWS Lambda, Azure Functions, and Google Cloud Functions." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 08 (2024): 1–13. http://dx.doi.org/10.55041/ijsrem36979.

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Serverless computing has revolutionized cloud services by abstracting infrastructure management, enabling developers to focus on application logic. This research examines the security and compliance features of three major serverless platforms: AWS Lambda, Azure Functions, and Google Cloud Functions. By evaluating authentication mechanisms, data encryption practices, vulnerability management, and compliance certifications, we aim to provide a comparative analysis that informs businesses and developers on the most secure and compliant platform for their needs. Keywords: Serverless Computing, Se

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Madnawat, Anshul. "Comparative Analysis of Sustainability, Carbon Footprint, and AI's Role in Reducing Emissions Across AWS, Azure, and Google Cloud." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 008 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem37115.

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The exponential expansion of cloud computing has greatly augmented worldwide energy consumption and carbon emissions. This research thoroughly examines the sustainability initiatives, carbon footprints, and the impact of AI in mitigating emissions in Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). This study assesses the measures employed by each provider to mitigate environmental effects by analysing both hypothetical and real-world data. The results emphasize combining AI- driven technologies and renewable energy to attain sustainability objectives. Key Words: Su

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Синюков, Д. С., and А. В. Потудинский. "Experimental study of the automatic troubleshooting system in the database." МОДЕЛИРОВАНИЕ, ОПТИМИЗАЦИЯ И ИНФОРМАЦИОННЫЕ ТЕХНОЛОГИИ 10, no. 1(36) (2022): 30–31. http://dx.doi.org/10.26102/2310-6018/2022.36.1.030.

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Современные приложения ориентированы на облачные сервисы для достижения лучшей производительности, географической репликации и снижения стоимости владения. Следуя существующим концепциям облачных сервисов, данное исследование использует богатые телеметрические данные и отображает рабочую нагрузку, выполняемую с использованием базы данных SQLкомпании Azure. Основной целью данного исследования является потенциальное улучшение как сервиса, так и обслуживания клиентов с помощью контролируемой платформы. Автоматическая система поиска неисправностей в базе данных предназначена для обнаружения пробле

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Pavlyha, Pavlo. "WAYS OF USING CLOUD SERVICES FOR TRAINING IT BACHELORS." Alfred Nobel University Journal of Pedagogy and Psychology 1, no. 29 (2025): 220–29. https://doi.org/10.32342/3041-2196-2025-1-29-19.

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The rapid evolution of information technologies (IT) necessitates continuous updates to educational programs to equip future specialists with relevant skills. Integrating modern cloud services into the training process for IT bachelors has become crucial for enhancing practical skills and ensuring graduates are com- petitive in the job market. This article explores the multifaceted application of cloud technologies in IT ed- ucation. The purpose of this study is to outline the ways cloud technologies can be applied in the preparation of IT bachelors across various specializations, compile a li

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Wong, Rou Yi, and Ping Ping Tan. "Receipt Image Extraction in Budgeting Mobile Application." Trends in Undergraduate Research 7, no. 1 (2024): c16–25. http://dx.doi.org/10.33736/tur.6110.2024.

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Money is spent and received almost daily. In most cases, receipts are issued after making a transaction. Budgeting mobile applications let users record these transactions for the purpose of tracking and managing their budget and money flow. The normal budgeting application let users input their transactions manually. In this paper, we proposed an improved feature: computer vision to capture the receipts and extract the data from the receipts.The technology used to extract the data of receipt is Microsoft Azure Form Recognizer which is a specialized Optical Character Recognizer (OCR) service th

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