CONNECTIVITY CONSTRAINT COMPUTING MARKET ANALYSIS

Market Challenges And Opportunities

Connectivity Constraint Computing Market Drivers:

• Increasing need to derive real-time actionable insights from large data volumes: Rapidly growing data volumes across industries is driving the need for advanced analytics solutions to derive real-time actionable insights. Connectivity constraint computing solutions enable organizations to identify complex patterns and relationships in data. According to Data growth worldwide report 2010-2025, the total amount of data created, captured, copied, and consumed globally is forecast to increase rapidly, reaching 64.2 zettabytes in 2020. For example, predictive maintenance in manufacturing has greatly benefited from edge computing solutions. Sensor data streaming from machines on the factory floor is analyzed locally instead of being sent to a remote datacenter. Their innovative edge-centric approaches are proving critical in enabling the next generation of data-driven businesses.

• Rising adoption of graph databases and graph analytics tools: The graph databases and analytics tools enable connections to be made between data that traditional databases cannot. The graph analytics market is projected to exhibit a CAGR of 22% from 2022 to 2030. Key market players are integrating graph analytics capabilities into their connectivity constraint computing solutions. According to report of Corinium, Gartner is a company that provides market intelligence, advisory services, and organizes events for the data and AI enterprise, predicting that the application of graph analytics will double annually through 2022. As more industries recognize the power of connected data models, the adoption of graph databases is projected to continue its rapid growth in the near future. Solution providers are throwing their resources behind research and development to enhance the capabilities of their graph analytic platforms.

• Growing focus on improving customer experience: Connectivity constraint computing helps uncover hidden insights about customer preferences and behaviors. These insights enable organizations to provide personalized recommendations and tailored offerings. For example, major e-commerce retailers and logistics firms providing services in connectivity challenged regions are deploying such solutions to allow their field agents to record transactions, place orders and synchronize critical data with the central systems, once the network is available. The global market is projected to witness robust double digit compounded annual growth between 2022 to 2025.
• Increasing need to prevent frauds: Connectivity constraint computing analyzes relationships and detects anomalies in data. This enables financial institutions and insurance companies to identify fraudulent activities in real-time. According to the data by International Telecommunication Union, the total number of cybercrime cases reported globally increased by over 17% between 2020 to 2022. This rise in fraudulent activities online has heightened the need for robust security and privacy measures. Controlled access architectures provide a reliable safeguard. With digital transformation continuing to deeply integrate into every industry, requirement of multilayered security solutions like connectivity constraint computing is set to steadily rise to mitigate fraud risks and ensure data and system integrity.

Connectivity Constraint Computing Market Opportunities:

• Leveraging artificial intelligence (AI) and machine learning algorithms: Integrating connectivity constraint computing with AI and machine learning algorithms can uncover more meaningful insights from complex data. It can enable real-time fraud prediction, improved sales forecasting, and better inventory management. International Business Machines (IBM) research used AI with graph analytics to predict wildfire spread patterns accurately. The International Telecommunication Union (ITU) expects AI to drive 80% of the value from future 5G networks as it helps optimize utilization of limited radio resources. This will allow telcos to efficiently support a massively increasing number of IoT endpoints per square km and unlock several new market opportunities.

• Increased adoption in healthcare sector: The healthcare sector is increasingly adopting connectivity constraint computing solutions to derive patient insights from large volumes of clinical, pharmaceutical and genomic data. It enables improved clinical decision making and better patient outcomes. The COVID-19 pandemic has further highlighted the need as well as opportunities for connectivity constraint solutions in healthcare. Social distancing norms during the pandemic necessitated greater adoption of telehealth and remote care models. According to the datapine report is a business intelligence and data visualization company, big data in healthcare is a term used to describe massive volumes of information created by the adoption of digital technologies that collect patients' records and help in managing hospital performance

• Growing application in predictive maintenance: Connectivity constraint computing can analyze the relationships between various operational data points. This enables manufacturing units to identify anomalies and predict maintenance needs in advance. As connectivity and computing resources continue to advance, predictive maintenance will move beyond detecting component failures to optimize life cycles and performance of entire production systems.

• Use in building smart cities: Governments across countries are opting for connectivity constraint computing to gain insights from massive volumes of transport, infrastructure, and utilities of data. These insights are being leveraged to optimize traffic patterns, electricity usage, and logistics for building smart-cities. Singapore government deployed graph analytics to improve water distribution efficiency. By 2025, the United Nations estimates 68% of the world's population will live in urban areas, thereby putting unprecedented stress on cities. Connectivity constrained solutions can help smart cities address this rise in population and demand more sustainably. They are crucial in expanding digital access to underserved communities and enabling next-gen applications around IoT, augmented reality/virtual reality (AR/VR) and edge AI that will define the future of urban living. Their deployment presents a major chance for growth in this area over the next decade as governments and companies work to build more inclusive, resilient and sustainable cities.

Connectivity Constraint Computing Market Restraints:

• Data security and privacy concerns: The risk of data breach and misuse of sensitive organizational data is restraining the adoption. Market players are addressing this by deploying security measures like encryption, access controls and data anonymization. Health Insurance Portability and Accountability Act (HIPAA) fined Premera Blue Cross US$6.85 Bn in 2021 for violation of privacy laws.
• Counterbalance: Conduct regular risk assessments to identify potential security and privacy weaknesses within the system and devise risk management strategies to address them and incorporate privacy considerations into the development of systems and devices from the ground up. This proactive approach ensures that privacy is a core element of product design and not an afterthought.
• Lack of skilled workforce: The lack of data science professionals with capabilities in advanced analytics like graph theory, modeling, statistics is challenging the market growth. Educational institutes lag in introducing connectivity constraint computing in their curriculum. According to report provided by LinkedIn is a business and employment-focused social media platform, graph analytics job openings grew over 50% in 2021.
• Counterbalance: Invest in cross-training current employees to handle roles that are associated with connectivity constraint computing. This can make the workforce more versatile and capable of managing different aspects of this niche market.
• High deployment costs: The costs involved in deploying connectivity constraint computing software, tools and infrastructure remains high for smaller organizations. The costs of migrating from legacy systems and integrating with existing IT systems are also substantial.
• Counterbalance: Conduct thorough cost-benefit analyses to identify the most cost-effective deployment strategies and to justify investments to stakeholders by highlighting the long-term benefits and savings