Developing scalable data solutions for small and medium enterprises: Challenges and best practices

International Journal of Management & Entrepreneurship Research, Год журнала: 2024, Номер 6(6), С. 1910 - 1935

Опубликована: Июнь 13, 2024

The rapid digital transformation sweeping across various industries has underscored the critical importance of data solutions for small and medium enterprises (SMEs). Developing scalable SMEs presents a unique set challenges requires adopting best practices tailored to their specific needs constraints. This review outlines aspects creating infrastructures SMEs, focusing on involved. Scalability in refers ability system handle growing amounts an increasing number users without compromising performance. For are vital as they provide flexibility expand operations adapt market changes efficiently. primary components such include storage, processing, analytics, security. Each component must be designed accommodate growth, ensuring remains efficient cost-effective business scales. face several developing solutions. Limited financial resources often restrict invest advanced technologies hire skilled personnel. Additionally, many lack in-house expertise required implement maintain complex systems. Data integration poses another significant challenge, particularly when dealing with disparate sources legacy Security compliance also present considerable hurdles, ensure meet regulatory standards extensive budgets or dedicated teams. Furthermore, scalability involves performance trade-offs, carefully balance cost, efficiency, future growth potential. Lastly, risk vendor lock-in can limit increase long-term costs, making it crucial choose technology partners wisely. To address these challenges, adopt practices. Conducting thorough assessment is essential align goals identify most requirements. Choosing right stack evaluating benefits cloud-based versus on-premises deciding between open-source proprietary software based budget Implementing robust management strategies, including governance quality management, ensures reliability integrity data. Effective techniques seamless accurate analytics. Leveraging cloud services advantageous offering infrastructure lower upfront costs. Selecting suitable service provider clear migration strategy significantly enhance flexibility. Ensuring security paramount; should strong measures, adhere requirements, conduct regular audits. Building team, either by investing training existing staff collaborating external experts, successful implementation Creating data-driven culture within organization drive better decision-making foster innovation. Monitoring optimizing solution continuously that meets evolving business. Utilizing analytics bottlenecks areas improvement help efficiency effectiveness. stay informed about trends solutions, artificial intelligence, machine learning, edge computing, multi-cloud remain competitive prepared growth. While enable them overcome obstacles harness power sustainable advantage. approach not only addresses current operational but positions demands technological advancements. Keywords: Scalable, Solution, Small Medium, Enterprise.

Язык: Английский

---

The role of data visualization in strategic decision making: Case studies from the tech industry

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(6), С. 1374 - 1390

Опубликована: Июнь 14, 2024

In the fast-paced and data-driven environment of tech industry, strategic decision-making is paramount for organizations to maintain relevance competitiveness. This paper investigates pivotal role data visualization in this process, leveraging a series illuminating case studies underscore its significance. Through real-world examples drawn from various sectors including software development, e-commerce, artificial intelligence, it elucidates how techniques enable unlock actionable insights complex sets. By transforming raw into visually intuitive representations, decision-makers can identify patterns, trends, correlations that inform direction drive improved business outcomes. The presented highlight diverse applications visualization, optimizing user experience on digital platforms predicting maintenance needs IoT devices. These showcase empowers make informed decisions across spectrum initiatives, product market analysis, resource allocation. Furthermore, delves challenges opportunities associated with implementing strategies, such as quality assurance, tool selection, training. It provides practical recommendations overcoming these obstacles maximizing effectiveness processes. shedding light transformative potential study not only underscores critical industry but also offers valuable seeking harness power navigating complexities today's landscape. comprehensive examination highlights need companies adopt advanced practices stay competitive innovative, ultimately contributing more data-informed agile organizational culture. explores technological advancements have propelled capabilities forward, machine learning, augmented reality, interactive dashboards. innovations enhanced ability analyze interpret vast amounts quickly accurately, further solidifying cornerstone planning. addresses human factors involved emphasizing importance design principles ensure clarity, accessibility, engagement. Effective visualizations present tell compelling story resonates stakeholders, facilitating shared understanding alignment around goals. roadmap looking integrate their frameworks. adopting best cutting-edge tools, enhance processes, innovation, edge ever-evolving detailed analysis insights, makes indispensable shaping future industry. Keywords: Data Visualization, Strategic Decision Making, Tech Industry, Case Studies, Business Intelligence.

Язык: Английский

---

Enhancing business intelligence in e-commerce: Utilizing advanced data integration for real-time insights

International Journal of Management & Entrepreneurship Research, Год журнала: 2024, Номер 6(6), С. 1936 - 1953

Опубликована: Июнь 13, 2024

This paper explores how advanced data integration techniques and real-time insights can significantly enhance BI in the e-commerce sector. By leveraging methods such as ETL, ELT, virtualization, API integration, streaming businesses achieve a comprehensive, unified view of their data. The enables dynamic pricing, personalized customer experiences, efficient inventory management, proactive fraud detection, improved support. Despite challenges silos, quality issues, scalability, security, technical complexity, solutions like governance, cloud computing, analytics tools address these obstacles. Future trends, including artificial intelligence, machine learning, edge block chains, fabric, promise to further transform e-commerce. Ultimately, are essential for companies stay competitive, optimize operations, satisfaction. In fast-paced competitive world e-commerce, ability make quick, informed decisions is crucial success. Business Intelligence (BI) plays vital role by transforming vast amounts into actionable that drive strategic operational efficiency. chain, Case studies from leading illustrate practical benefits implementing techniques, showcasing significant improvements efficiency Keywords: Intelligence, E-commerce Analytics, Data Integration, Real-Time Insights.

Язык: Английский

---

Leveraging big data for agile transformation in technology firms: Implementation and best practices

Engineering Science & Technology Journal, Год журнала: 2024, Номер 5(6), С. 1952 - 1968

Опубликована: Июнь 13, 2024

The rapid pace of technological advancements and the increasing demand for innovation have compelled technology firms to adopt Agile methodologies, which promote flexibility, speed, customer-centric development. Concurrently, explosion Big Data has provided these with unprecedented opportunities enhance their decision-making processes, optimize operations, gain deeper insights into market customer behaviors. This review explores integration transformation in firms, emphasizing implementation strategies best practices maximize benefits both paradigms. involves shifting from traditional, linear development processes iterative incremental methodologies that facilitate continuous improvement adaptation. Data, characterized by its volume, velocity, variety, veracity, offers valuable can drive more informed strategic within frameworks. significantly product cycles, improve satisfaction, streamline operations. requires a well-defined strategy includes setting clear objectives, building robust data infrastructure, ensuring quality security. Establishing success metrics aligned business goals is crucial measuring impact initiatives. Building scalable infrastructure deploying advanced collection, storage, processing solutions handle diverse voluminous typical firms. Ensuring integrity essential deriving accurate inform processes. Integrating incorporating analytics ceremonies such as sprint planning, reviews, retrospectives. facilitates real-time feedback delivery, allowing teams respond swiftly changes products iteratively. Developing competency another critical aspect, requiring investments training, upskilling employees, hiring science talent interpret leverage effectively. Best leveraging include cultivating data-driven culture encourages literacy promotes transparency collaboration across organization. Advanced artificial intelligence (AI) play pivotal role harnessing predictive enabling proactive decision-making. Implementing visualization tools helps understand complex patterns trends, enhancing ability make decisions. An approach recommended, starting pilot projects test refine initiatives before scaling them Regularly monitoring key performance indicators (KPIs) ensures remain objectives allows timely adjustments based on results. Collaboration stakeholders, including cross-functional customers, vital are effectively integrated efforts align needs. future looks promising, emerging technologies Internet Things (IoT), blockchain, AI poised further capabilities. However, must also navigate ethical legal considerations, privacy compliance, ensure responsible use analytics. Leveraging powerful combination adaptability, insights. By adopting adhering practices, achieve significant operational efficiencies, enhanced development, improved positioning themselves sustained rapidly evolving landscape. Keywords: Transformation, Technology Firm, Practices.

Язык: Английский

---

Optimizing healthcare resource allocation through data-driven demographic and psychographic analysis

Computer Science & IT Research Journal, Год журнала: 2024, Номер 5(6), С. 1488 - 1504

Опубликована: Июнь 25, 2024

This paper explores the multifaceted nature of healthcare resource allocation, examining demographic and psychographic analysis, data sources analysis techniques, challenges, future directions, innovations. Demographic provides insights into population characteristics, demand, disparities, informing targeted allocation strategies. Psychographic complements by elucidating patient attitudes, behaviors, preferences, guiding personalized care delivery intervention design. A diverse array sources, including electronic health records, surveys, geospatial data, underpins allocation. Advanced techniques such as predictive analytics machine learning unlock actionable from these enabling proactive optimization. Challenges quality, bias, ethical considerations underscore complexity However, emerging innovations, artificial intelligence, precision medicine, value-based models, offer transformative potential for optimizing improving outcomes. Looking ahead, integration innovative technologies patient-centered models promises to reshape emphasizing equity, efficiency, engagement. By navigating challenges thoughtfully embracing opportunities, systems can enhance strategies better meet evolving needs patients communities. administrative databases, social determinants analytics, learning, spatial simulation modeling Keywords: Healthcare Resource Allocation, Analysis, Data Sources, Analysis Techniques, Future Directions.

Язык: Английский

---

Building sustainable business models with predictive analytics: Case studies from various industries

International Journal of Advanced Economics, Год журнала: 2024, Номер 6(8), С. 394 - 406

Опубликована: Авг. 22, 2024

Predictive analytics has emerged as a powerful tool for businesses across various industries to build sustainable business models. This review provides insights into the significance of predictive in fostering sustainability and showcases case studies from different sectors where been effectively employed. enables anticipate future trends, identify potential risks, make data-driven decisions, thereby enhancing operational efficiency, improving customer experiences, driving growth. By leveraging historical data advanced statistical algorithms, organizations can gain valuable consumer behavior, market dynamics, processes. In retail industry, facilitates segmentation targeted marketing campaigns optimizes inventory management through demand forecasting. These initiatives result increased revenue, reduced costs, improved satisfaction. healthcare sector, aids disease prediction prevention, enabling early detection health risks proactive interventions. Additionally, models optimize hospital resource management, leading enhanced efficiency patient outcomes. Financial services leverage credit risk assessment, fraud detection, personalized financial services. accurately assessing creditworthiness, detecting fraudulent activities, offering tailored products, institutions mitigate improve regulatory compliance, enhance manufacturing is utilized maintenance supply chain optimization. reduces downtime costs by predicting equipment failures, while optimization improves sourcing, production, distribution processes, resulting streamlined operations profitability. Overall, integration fosters informed resources, meet evolving needs. highlight transformative impact building long-term success.. Keywords: Business Model, Analysis, Case Studies, Industries.

Язык: Английский

---

Data-Driven approaches to improve customer experience in banking: Techniques and outcomes

International Journal of Management & Entrepreneurship Research, Год журнала: 2024, Номер 6(8), С. 2797 - 2818

Опубликована: Авг. 30, 2024

The banking industry is undergoing a significant transformation driven by the integration of data-driven approaches aimed at enhancing customer experience. This evolution essential for banks to maintain competitive advantage, foster loyalty, and adapt rapidly changing digital landscape. By leveraging vast amounts data, can gain profound insights into behavior, preferences, needs, enabling delivery more personalized, efficient, secure services. review delves key techniques employed in consequential outcomes. Advanced data analytics allows segment their base distinct groups based on demographics, behaviours, financial needs. Techniques such as machine learning algorithms clustering identify patterns within facilitating creation targeted products For instance, solutions be specifically designed tech-savvy millennials, while tailored advice might suitable older customers. segmentation helps addressing unique needs different effectively. Utilizing historical predictive models forecast future behaviors trends. capability enables anticipate predicting which customers interested applying mortgage or those who could benefit from advisory Predictive also aids identifying risk churn, allowing implement retention strategies proactively. Through insights, offer highly personalized experiences. Recommendation systems, akin used leading e-commerce platforms, suggest relevant services individual profiles transaction histories. level personalization not only enhances experience but increases likelihood successful cross-selling upselling efforts. Employing Natural Language Processing (NLP) sentiment analysis, analyze feedback various sources, including social media, surveys, call center interactions. Understanding promptly address issues, improve service quality, build stronger, positive relationships with Data-driven are pivotal mitigating fraudulent activities. Machine detect anomalies indicative fraud. Real-time monitoring systems flag suspicious activities, thereby protecting maintaining trust system. Personalized proactive offerings significantly boost satisfaction. Customers appreciate experiences quick resolution higher levels satisfaction increased brand loyalty. Automation routine tasks maintenance streamline operations. efficiency reduces workload bank staff, them focus complex resulting cost savings improved delivery. real-time strengthen management capabilities. Banks better assess credit risks, manage fraud, ensure compliance regulatory requirements, thus safeguarding assets reputation. Effective targeting drive product uptake retention. Enhanced opportunities contribute revenue growth profitability, match Insights derived inform development new evolving continuous innovation keeps providing application advanced analytics, learning, NLP boosts loyalty drives operational efficiency, improves management, fosters growth. As continue innovate strategies, appears promising dynamic. ability evolve technological advancements will crucial customer-centric staying ahead sector. Keywords: Data-Driven, Banking, Customer Feedback.

Язык: Английский

---

DECODING DIGITAL BUSINESS STRATEGIES: INSIGHTS FROM FIVE YEARS OF RESEARCH

Deleted Journal, Год журнала: 2024, Номер 3 (03), С. 124 - 134

Опубликована: Окт. 11, 2024

The contemporary business environment is characterized by its dynamic nature, driven rapid technological advancements, necessitating enterprises to adapt their operational frameworks continually sustain competitiveness and relevance. Consequently, the formulation of a robust digital strategy becomes imperative, serving as strategic necessity effectively navigate intricacies era. Given swift pace metamorphosis accelerated proliferation emerging technologies, notably artificial intelligence, systematic examination scholarly literature on strategies indispensable discern current trends inform decision-makers promptly. This investigation endeavors delineate prominent research clusters influential figures within realm strategy, elucidate fundamental concepts underpinning strategies, thereby construct comprehensive framework encapsulating foundational principles this domain. study conducts bibliometric analysis Web Science publications pertaining Digital Business Strategy Management disciplines, focusing works indexed over preceding five years utilizing Biblioshiny application. findings underscore burgeoning interest in subject, collaboration, significant internationalization landscape. Noteworthy contributions emanating from countries such China, United Arab Emirates, Italy, Jordan, Kingdom ascent new frontrunners arena highlight transformative influence technologies reshaping global competitiveness. Central themes include implementation (performance), recognition innovative essence changes imperative for innovation, pivotal role marketing, opportunities SMEs. Fundamentally, these inquiries are anchored technology, impact assessment, understanding flexibility management practices. key components successful focus innovation alongside considerations performance impact. intimately intertwined with marketing methodologies, social media platforms, model innovations, optimization supply chain operations. insights gleaned endeavor could serve guide navigating offer valuable direction future

Язык: Английский

---

Digital Transformation as a Factor in The Economic Development of Montenegro

Advances in electronic commerce (AEC) book series/Advances in electronic commerce series, Год журнала: 2024, Номер unknown, С. 81 - 112

Опубликована: Ноя. 8, 2024

Digital transformation in Montenegro is an evolving process that aims to use digital technologies boost economic growth, improve governance, enhance public services and foster innovation. The main objective of this chapter analyze the impact administration reform as a determinant Montenegro's development on achieved social results, which are determined by level various key parameters, such as: GDP, FDI, import export goods services. In context, special emphasis was placed analysis two indicators: EGDI (E-Government Development Index) EPI (E-Participation Index). methodological concept first part based official data from World Bank Monstat, while second UN eGovernment Survey, report United Nations (UN E-Government Knowledgebase). period covered survey 2012 2023. results show important factor for development.

Язык: Английский

---