Standards-based enterprise architecture for Iran's distribution system operators: A comparative assessment

As enterprises transition toward cloud-native infrastructures, Business Intelligence (BI) systems must be re-architected to leverage the scalability, flexibility, and agility of cloud platforms. This paper investigates the architectural considerations and challenges of deploying Oracle BI Cloud Service (BICS) in a cloud-native paradigm. It critically examines performance optimization strategies, security frameworks, and data integration mechanisms crucial for building resilient BI ecosystems. The study adopts a mixed-methods approach, combining architectural analysis, performance benchmarking, and security evaluation to explore the multifaceted aspects of BI cloud migration. Findings reveal that while Oracle BICS provides robust native tools for scalability and integration, significant challenges persist in data latency, compliance, and hybrid-cloud compatibility. The paper proposes an optimized architecture model and best practice guidelines to aid enterprise architects and data engineers in future-proofing their BI strategies in the evolving cloud landscape.

Modern-day web applications are facing an array of continuously evolving URL-based threats, including malicious payloads hidden in query strings and automated bots that probe for vulnerable endpoints. In this whitepaper, we will explore the necessity of URL protection in today's web environments and how Web Application Firewalls (WAFs) can be effectively integrated. We will discuss the capabilities of WAF, rule-based filtering, anomaly detection, request normalization, and how these capabilities will complement the URL protection techniques (URL rewriting, filtering, obfuscation, encoding normalization, and real-time monitoring). Real-world use cases from leading providers such as Cloudflare, AWS, Imperva, etc., will be examined to illustrate the implementation strategies in enterprise, hybrid, and cloud native architectures. We compare the methods like URL rewriting vs. filtering and evaluate the trade-offs with the top solutions, highlighting how a combined approach can mitigate the attacks without compromising on performance and flexibility. Through blending the research insights and the best technical practices, this paper provides a comprehensive understanding of how to integrate URL protection with WAFs and secure web applications at scale.

The modern enterprise landscape demands architectural flexibility that transcends traditional single-vendor cloud strategies. Organizations increasingly recognize that optimal digital transformation requires leveraging the unique strengths of multiple cloud providers while maintaining operational coherence and strategic alignment. This whitepaper presents a comprehensive analysis of enterprise architecture patterns for deploying Microsoft Dynamics 365 Customer Engagement (D365 CE) within hybrid environments that strategically combine Amazon Web Services (AWS) and Microsoft Azure capabilities.

This article reviews the modernization of enterprise Volume Licensing Service Center and Next Generation Volume Licensing platforms during 2010–2015, highlighting a 67% reduction in release cycle time and a 30% decrease in post-release defects through incremental architectural refactoring, build automation via Team Foundation Server, and Security Development Lifecycle integration. The transformation addressed critical challenges in legacy monolithic architectures, transitioning from quarterly to monthly release schedules while maintaining operational stability for platforms supporting billions in annual enterprise revenue. Key technical implementations include ASP.NET WebForms-to-MVC migration patterns, WCF service integration architecture, TFS-based XAML build definitions, PowerShell deployment automation, and SDL-compliant static analysis workflows. This comprehensive review provides practical guidance for enterprise architects and engineering leaders managing platform modernization initiatives in regulated environments where incremental transformation strategies must balance innovation velocity with operational stability and compliance requirements.

Enterprise architectures with multiple clouds have brought unprecedented complexity to cryptographic security management, demanding out-of-the-box solutions that go beyond the old perimeter-based protection frameworks. The coming together of artificial intelligence and innovative cryptographic methods in protecting distributed cloud environments places high emphasis on homomorphic encryption, quantum-resistant cryptography, and self-response attack mechanisms. Cryptographic protocols integrated with machine learning models bring about dynamic key management, anomaly detection in real time, and adaptive security states reacting to changing threat profiles. Modern multi-cloud ecosystems require cryptographic frameworks that preserve data secrecy across disparate platforms with varied regulatory requirements across multiple jurisdictions. Modern advancements in AI-boosted cryptographic architecture show promise in safeguarding enterprise data across cloud borders, but there remain crucial challenges in deploying threat-resilient automation systems. Effective next-generation security deployments demand effortless collaboration among cryptographic primitives, smart automation layers, and complete governance frameworks that balance technical and organizational aspects of multi-cloud security. Zero-trust design principles remove implicit trust assumptions by using continuous verification measures, while federated learning methods facilitate collaborative security optimization without centralizing the sensitive operational information. Quantum key distribution and blockchain-based key management are new technologies that hold the promise of overcoming current constraints in multi-cloud cryptographic deployments.

The Career Development Center (CDC) at Ma’soem University supports students and alumni in preparing for the workforce through services such as counseling, psychological testing, tracer studies, and job vacancy information. However, the absence of an integrated system makes these services less efficient and difficult to manage. This study proposes a centralized information system using the Enterprise Architecture Planning (EAP) approach to support the CDC’s digital transformation. The design includes data, application, and technology architectures aimed at improving service delivery and operational performance. The system development process involves observation, interviews, business process modeling (BPMN), and data structure design (ERD). The result is a system design with key modules supported by secure technological infrastructure. The system is planned to be implemented in stages and is expected to help the CDC operate more effectively and align with the needs of the industrial sector.

Sustainable Enterprise Architecture: Embedding Circular Economy and Lifecycle Thinking in IT Strategy

This article examines the evolution of state management solutions in large-scale enterprise frontend applications, focusing on NgRx (Angular), Redux (React), and Pinia (Vue). Beginning with the conceptual shift from MVC to Flux/Redux patterns, the article explores how each framework-specific implementation addresses complex state challenges through different architectural approaches. NgRx leverages RxJS to create a reactive state system aligned with Angular's design philosophy, while Redux has evolved through Redux Toolkit to improve developer experience while maintaining its core principles. Pinia represents Vue's modern approach, emphasizing simplicity and developer experience without sacrificing power. Through comparative analysis of architectural patterns, performance characteristics, and developer experience metrics, the article provides decision frameworks for enterprise architects selecting appropriate state management solutions based on framework alignment, application complexity, and team dynamics. The analysis extends beyond theoretical comparisons to include practical implementation considerations, identifying key trade-offs in complexity versus flexibility, initial development speed versus long-term maintainability, and framework-specific optimizations that impact both runtime performance and developer productivity across the application lifecycle from initial architecture to ongoing maintenance and feature expansion.

Standardising digital health interventions in Uganda’s health system using an enterprise architecture approach

Strategic Information Systems (IS) and Information Technology (IT) planning play a vital role in aligning technological initiatives with business objectives, particularly in asset-intensive industries. This study aims to implement the TOGAF ADM framework to design a strategic IS/IT planning model for a heavy equipment rental company, demonstrating how enterprise architecture can align IT initiatives with business goals. PT. XYZ has not yet implemented an information system strategy for the company’s needs in terms of management, leading to inefficiencies in business operations at PT. XYZ. A qualitative approach was used to obtained through in-depth interviews with company’s owners and managers, observation data of company’s IT asset also collected to describe organization’s current IS/IT landscape and applies the TOGAF ADM phases to design an enterprise architecture that supports business-IT alignment. This study demonstrates how TOGAF ADM can provide a structured methodology for identifying business needs, defining architectural visions, and developing a roadmap for IS/IT improvements. Findings indicate that using EA frameworks such as TOGAF ADM enhances strategic planning capabilities, supports organizational agility, and provides a repeatable model for similar enterprises in the rental or industrial sector. The results offer valuable insights for practitioners and researchers interested in applying enterprise architecture to improve IS/IT strategic planning processes.

Strategic Information Systems (IS) and Information Technology (IT) planning play a vital role in aligning technological initiatives with business objectives, particularly in asset-intensive industries. This study aims to implement the TOGAF ADM framework to design a strategic IS/IT planning model for a heavy equipment rental company, demonstrating how enterprise architecture can align IT initiatives with business goals. PT. XYZ has not yet implemented an information system strategy for the company’s needs in terms of management, leading to inefficiencies in business operations at PT. XYZ. A qualitative approach was used to obtained through in-depth interviews with company’s owners and managers, observation data of company’s IT asset also collected to describe organization’s current IS/IT landscape and applies the TOGAF ADM phases to design an enterprise architecture that supports business-IT alignment. This study demonstrates how TOGAF ADM can provide a structured methodology for identifying business needs, defining architectural visions, and developing a roadmap for IS/IT improvements. Findings indicate that using EA frameworks such as TOGAF ADM enhances strategic planning capabilities, supports organizational agility, and provides a repeatable model for similar enterprises in the rental or industrial sector. The results offer valuable insights for practitioners and researchers interested in applying enterprise architecture to improve IS/IT strategic planning processes.

Despite its growth and resilience over the last decades, the cruise industry faces significant challenges in its strategic, operational, and technology domains. The unique complexity of the industry requires cruise companies to adopt a structured approach to enterprise transformation. To address this problem, this aims to provide an Enterprise Architecture (EA) blueprint for the cruise industry. Using a case study of a leading cruise line, CruiseX, this study analyzes the operational model of the cruise line and apply two industry-leading standards: The Open Group Architecture Framework (TOGAF) and the ArchiMate modelling language. This study applies the four core phases of TOGAF Architecture Development Method (ADM) from the initial phase of Architecture Vision (Phase A), through the definition of Business Architecture, Information System Architecture, and Technology Architecture (Phase B to D). The ArchiMate language is utilized to visualize the core business processes, information systems, and technology architecture. By using TOGAF ADM as the technical guidelines and ArchiMate as the modeling language, the result of this study is a blueprint of core business processes, application and data that support each business processes, and the underlying technology infrastructure, that provides a structured framework and serves as an actionable tool for implementing enterprise architecture in cruise industry. This research also extends the application of TOGAF and ArchiMate to the under-research cruise industry domain. The study’s limitations include the reliance on publicly available data, the limited scope of business processes, and the lacks of practitioner validation, suggesting clear directions for future research.

This article presents a comprehensive framework of design principles for developing scalable enterprise applications in financial cloud environments, addressing the fundamental transformation occurring as financial institutions migrate from traditional on-premises infrastructure to cloud-native architectures. The article explores how established architectural patterns, including Command Query Responsibility Segregation (CQRS), event sourcing, and polyglot persistence, can be effectively implemented alongside modern technologies such as Kubernetes container orchestration and infrastructure-as-code practices. Through an examination of core architectural principles, including stateless services, loose coupling, and domain-driven design, the article demonstrates how financial organizations can balance cloud-native principles with stringent regulatory requirements for transactional integrity, audit capabilities, and data sovereignty. The framework addresses critical compliance and governance challenges through zero-trust security architectures and comprehensive audit trail mechanisms while providing practical guidance for implementing resilience patterns that ensure continuous operation across distributed systems. By integrating GitOps practices for continuous deployment and advanced observability strategies, the proposed approach enables financial institutions to achieve operational excellence while maintaining the reliability and security standards essential for financial services, ultimately providing enterprise architects and engineers with actionable strategies for building robust, compliant, and innovative financial applications in the cloud.

Extreme weather events, pandemics, and economic disruptions inflict serious damage on vulnerable communities by interrupting access to vital healthcare and financial services. Traditional enterprise systems including SAP ERP, Oracle Database clusters, and Salesforce CRM demonstrate critical architectural limitations during crisis events, with conventional load balancing technologies such as HAProxy and NGINX failing when primary data centers become inaccessible. The Resilient AI Enterprise Architecture (RAIEA) framework addresses these fundamental gaps through three key technological pillars implemented via comprehensive modern technology stacks: A) Edge Intelligence Integration utilizing Kubernetes-native orchestration through K3s and MicroK8s, with Docker and Podman providing containerized service isolation across AWS IoT Greengrass, Azure IoT Edge, and Google Cloud IoT Core managed edge computing platforms; B) AI-Based Predictive Load Distribution employing TensorFlow Lite and PyTorch Mobile for edge-optimized machine learning inference, with Apache Kafka and RabbitMQ enabling real-time data streaming between distributed nodes; and C) Context-Aware Service Reconfiguration integrating Istio and Linkerd service mesh technologies with Kong and Envoy Proxy API gateways for dynamic traffic routing based on real-time crisis conditions. Real-world deployments demonstrate significant performance enhancements: Philippines' RapidPro operates on Django/Python with PostgreSQL and Redis integration, Colombia's Plan Maestro utilizes Spring Boot/Java microservices with Apache Kafka event streaming, and the UN Digital Refugee ID Platform employs Node.js/Express.js with MongoDB and biometric SDKs including Neurotechnology VeriLook. The framework incorporates comprehensive ethical service delivery mechanisms through algorithmic fairness techniques, Prometheus and Grafana monitoring systems, and automated compliance monitoring via Apache Superset and RegTech platforms including Thomson Reuters Regulatory Intelligence. Policy alignment with international frameworks such as the Sendai Framework for Disaster Risk Reduction, supported by HashiCorp Vault cryptographic key management and Hyperledger Fabric blockchain audit trails, enables scalable adoption through Digital Crisis Regulation Zones and automated regulatory compliance systems.

The advancement of information technology requires educational institutions to manage data and business processes more efficiently and in an integrated manner. MA Al Hidayah, as a private Islamic senior high school, faces challenges in handling academic and administrative data, which are still mostly managed manually and lack integration. This study aims to design an information system architecture using the Enterprise Architecture Planning (EAP) method as a solution to support the institution’s vision, mission, and operational needs. The EAP approach consists of four layers: planning initiation, current business and system modeling, architecture design (data, application, and technology), and implementation and migration planning. The results of this study include a blueprint for data, application, and technology architecture, along with implementation strategies and human resource requirements. The proposed architecture is expected to serve as a guide in building an integrated information system that enhances operational efficiency, information transparency, and data-driven decision-making at MA Al Hidayah.

Abstract This systematic literature review (SLR) examines how digitalization shapes the financial performance of businesses by synthesizing research published from 2014 to 2024. The study analysed 30 articles and utilized the adaptive enterprise architecture (EA) framework to categorize findings across various layers: interaction, human, technology, environment, and security. Key findings from prior literature indicate that digitalization significantly enhances financial performance through improved profit levels, sales growth, and market share, among others, with questionnaire surveys being the predominant method for measurement. The study reveals notable gaps in the literature, particularly regarding the technology, environment, and security layers, and opens the need for further systematic research with the help of EA framework. The future studies should investigate how digitalization affects financial performance over the long run, specifically focussing on market competitiveness, Return on Investment (ROI), and sustainable profitability. Longitudinal research could provide a more thorough picture of how digitalization affects financial outcomes over time.

The need for Information Technology to support an organization's business processes must be clearly defined so that development targets can be aligned with the organization's needs and capabilities. The Selangor Theatre Council (MTS) Malaysia is an organization that coordinates theater arts in Selangor, Malaysia, which has 12 theater branches. To facilitate organizational promotion, activity promotion, and good data integration, technology utilization is required. This study uses the Design Science Research (DSR) method with stages of identifying problems and objectives, developing design, presenting results and evaluating, and the TOGAF Framework for designing Enterprise Architecture Design. The results of this study are in the form of enterprise architecture design recommendations. At the problem identification stage, data on the need for information technology utilization in each business process was obtained by 74% through a questionnaire survey. At the design development stage, resulting in an Architecture Vision, a formulated strategy identification is carried out so that the vision, mission and objectives of the organization can be achieved by analyzing internal and external conditions and the Value Chain strategic grid. Business architecture design is carried out by mapping the ongoing business processes with the development plan and the readiness of existing resources in MTS so that GAPs will be found. Data/information architecture design maps information needs in each business process. Application architecture design maps application development needs and technology architecture design maps the needs of the technology used. In the final stage, the design results are presented using the results presentation technique and filling out a questionnaire for compliance with the results of 89%.

This research examines enterprise network architecture transformation through cloud computing and Software-Defined Networking implementation using systematic literature review approach. The research methodology applies PICO framework with analysis of 10 high-quality articles from reputable academic databases spanning 2019-2024. Research findings identify that cloud computing and SDN integration creates synergy enabling organizations to achieve significant automation and efficiency levels. Critical success factors for transformation include social influence, facilitating conditions, and effective enterprise architecture implementation. Holistic virtualization and pervasive intelligence become primary enablers in achieving optimal network flexibility. Development prospects demonstrate emerging technology convergence with digital twin paradigm and model-driven techniques as central components of future architecture. This research contributes to understanding enterprise network transformation dynamics and provides comprehensive implementation framework for organizational adoption.

The enterprise deployment of artificial intelligence language models presents organizations with critical architectural decisions between Small Language Models and Large Language Models, each offering distinct advantages and operational considerations. Small Language Models, characterized by parameter counts ranging from millions to several billion, provide computational efficiency, rapid deployment capabilities, and cost-effective solutions for real-time applications requiring millisecond response times. Large Language Models, featuring billions to trillions of parameters, deliver sophisticated contextual understanding, complex reasoning abilities, and comprehensive knowledge bases suitable for advanced content generation and analytical tasks. Enterprise environments must evaluate infrastructure requirements, with Small Language Models operating effectively on standard CPU configurations and minimal memory footprints, while Large Language Models demand GPU clusters and substantial computational resources. The architectural choice significantly impacts system performance, operational costs, scalability potential, and long-term strategic positioning. Contemporary enterprise implementations increasingly recognize hybrid deployment strategies that leverage the complementary strengths of both model categories, enabling organizations to optimize resource utilization while addressing diverse application requirements. Future developments in neural architecture search, hardware-software co-design methodologies, and federated learning frameworks promise to reshape enterprise AI deployment strategies, creating opportunities for more efficient and scalable artificial intelligence solutions.