Key Mobile Payments StatisticsTop Mobile Payments AppsFinance App Market LandscapeMobile Payments Transaction VolumeMobile Payments UsersMobile Payments Adoption by CountryMobile Payments TPV in...

This dataset offers a historical perspective on the evolution of the mobile operating system market over time. By tracking the market share of each OS, it provides insights into consumer preferences, technological advancements, and the competitive landscape within the mobile industry.

For data scientists and analysts, this is valuable for conducting trend analysis, forecasting future market dynamics, and understanding the factors driving changes in OS popularity. It can be used to:

• Analyze trends in mobile OS adoption and decline over time.
• Forecast future shifts in the mobile OS market.
• Assess the impact of new OS releases, features, or other market entrants on existing OS market shares.
• Compare the growth rates of different operating systems.

Several analyses can be conducted, including:

• Identify which operating systems have gained or lost market share over time and the rate of these changes.
• Determine periods during which certain operating systems dominated the market and analyze the causes behind such dominance.
• Compare the year-over-year growth rates of different operating systems to identify which ones are gaining momentum.
• Use historical data to forecast future trends in the mobile OS market.

The smartphone penetration in the United States was forecast to continuously increase between 2024 and 2029 by in total 1.3 percentage points. The penetration is estimated to amount to 97 percent in 2029. Notably, the smartphone penetration of was continuously increasing over the past years.The penetration rate refers to the share of the total population.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the smartphone penetration in countries like Mexico and Canada.

Dataset

This dataset was created by Pritam Dahal

Contents

Techsalerator’s Business Technographic Data for Vietnam: Unlocking Insights into Vietnam's Technology Landscape

Techsalerator’s Business Technographic Data for Vietnam provides a detailed and comprehensive dataset essential for businesses, market analysts, and technology vendors seeking to understand and engage with companies operating within Vietnam. This dataset offers in-depth insights into the technological landscape, capturing and organizing data related to technology stacks, digital tools, and IT infrastructure used by businesses in the country.

Please reach out to us at info@techsalerator.com or visit Techsalerator Contact.

Top 5 Most Utilized Data Fields

• Company Name: This field lists the names of companies in Vietnam, enabling technology vendors to target potential clients and allowing analysts to assess technology adoption trends within specific businesses.

• Technology Stack: This field outlines the technologies and software solutions a company uses, such as accounting systems, customer management software, and cloud services. Understanding a company's technology stack is key to evaluating its digital maturity and operational needs.

• Deployment Status: This field indicates whether the technology is currently deployed, planned for future deployment, or under evaluation. Vendors can use this information to assess the level of technology adoption and interest among companies in Vietnam.

• Industry Sector: This field specifies the industry in which the company operates, such as manufacturing, retail, or finance. Knowing the industry helps vendors tailor their products to sector-specific demands and emerging trends in Vietnam.

• Geographic Location: This field identifies the company's headquarters or primary operations within Vietnam. Geographic information aids in regional analysis and understanding localized technology adoption patterns across the country.

Top 5 Technology Trends in Vietnam

• E-commerce Expansion: With a rapidly growing digital consumer base, Vietnamese companies are increasingly investing in e-commerce platforms, digital marketing, and online payment systems to capture a larger market share and enhance customer experience.

• Fintech Innovations: Vietnam’s fintech sector is experiencing significant growth, with businesses adopting advanced financial technologies such as mobile payment solutions, digital wallets, and blockchain to improve financial transactions and services.

• Smart Manufacturing: The manufacturing sector in Vietnam is embracing Industry 4.0 technologies, including automation, IoT, and AI-driven analytics, to enhance productivity, efficiency, and competitiveness in the global market.

• Cloud Computing and SaaS: Cloud-based solutions and Software-as-a-Service (SaaS) offerings are gaining traction, providing Vietnamese businesses with scalable and flexible IT infrastructure that supports remote work and digital transformation initiatives.

• Cybersecurity Enhancements: As digital activities increase, so does the need for robust cybersecurity measures. Companies in Vietnam are investing in advanced security solutions, including threat detection systems and data protection tools, to safeguard their operations and customer data.

Top 5 Companies with Notable Technographic Data in Vietnam

• Vietcombank: A leading financial institution, Vietcombank is implementing cutting-edge digital banking solutions, including mobile banking apps and secure online transaction systems, to enhance customer service and operational efficiency.

• Vingroup: As a major conglomerate, Vingroup leverages advanced technologies across its diverse business segments, including real estate, retail, and healthcare, integrating smart technologies and digital platforms into its operations.

• FPT Corporation: A major IT services and software development company, FPT is at the forefront of digital transformation in Vietnam, offering solutions in cloud computing, AI, and cybersecurity to both domestic and international clients.

• Masan Group: A leading consumer goods and retail company, Masan Group is adopting digital tools and e-commerce platforms to optimize its supply chain, enhance customer engagement, and drive business growth.

• VNPT: Vietnam’s largest telecommunications provider, VNPT is expanding its network infrastructure and investing in advanced technologies such as 5G and IoT to improve connectivity and support the digital economy.

Accessing Techsalerator’s Business Technographic Data

For those interested in accessing Techsalerator’s Business Technographic Data for Vietnam, please contact info@techsalerator.com with your specific needs. Techsalerator offers customized quotes based on the required number of data fields and records, with datasets available for delivery within 24 hours. Ongoing access ...

The population share with mobile internet access in India was forecast to continuously increase between 2024 and 2029 by in total 25 percentage points. After the fifteenth consecutive increasing year, the mobile internet penetration is estimated to reach 73.62 percent and therefore a new peak in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the population share with mobile internet access in countries like Bangladesh and Sri Lanka.

This dataset offers a comprehensive overview of the iPhone's journey in the global smartphone market from 2010 to 2024 . It includes:

📊 Number of iPhone Users: Total users worldwide and within the USA. 📈 Sales Figures: Yearly iPhone sales data. 🏆 Market Share: Comparison of iOS and Android market shares across years. This dataset is perfect for:

Market forecasting and trend analysis. Competitive landscape studies between iOS and Android. Consumer behavior research in the tech industry. Whether you're a data scientist, market analyst, or tech enthusiast, this dataset provides valuable insights to support your research and projects.

Mobile Robot Dataset Versioning Market Outlook

According to our latest research, the Global Mobile Robot Dataset Versioning market size was valued at $327 million in 2024 and is projected to reach $1.26 billion by 2033, expanding at a robust CAGR of 16.7% during the forecast period of 2025–2033. The primary growth driver for this market is the increasing adoption of advanced robotics across industries, which demands reliable, scalable, and version-controlled datasets to fuel AI and machine learning algorithms for mobile robots. As industries accelerate their automation initiatives, the need for accurate, up-to-date, and well-managed datasets becomes critical to ensuring operational efficiency, safety, and performance of mobile robotic systems. This trend is further amplified by the proliferation of autonomous systems in logistics, healthcare, and manufacturing, where real-time data integrity and traceability are essential.

Regional Outlook

North America currently holds the largest share of the global Mobile Robot Dataset Versioning market, accounting for approximately 38% of total market value in 2024. The region’s dominance is underpinned by its mature technology ecosystem, significant investments in robotics research, and widespread adoption of mobile robots across sectors such as logistics, automotive, and healthcare. Leading technology companies and research institutes in the United States and Canada are at the forefront of developing sophisticated dataset versioning solutions, leveraging advanced cloud infrastructure and robust cybersecurity frameworks. Additionally, supportive government policies and funding for AI and robotics innovation have accelerated the deployment of dataset versioning tools, making North America a pivotal hub for market growth and technological advancement.

In contrast, the Asia Pacific region is emerging as the fastest-growing market, projected to register an impressive CAGR of 19.4% from 2025 to 2033. This rapid expansion is driven by escalating investments in automation, particularly in China, Japan, and South Korea, where manufacturing and logistics sectors are undergoing digital transformation. The region benefits from a burgeoning startup ecosystem, increased government support for Industry 4.0 initiatives, and a rising demand for smart warehouses and autonomous vehicles. As regional enterprises accelerate the integration of mobile robots, the need for scalable, cloud-based dataset versioning solutions becomes paramount, fueling market growth. Furthermore, collaborations between local universities, global tech giants, and government agencies are fostering innovation and accelerating the adoption of best practices in data management and version control.

Emerging economies in Latin America, the Middle East, and Africa are witnessing gradual adoption of mobile robot dataset versioning solutions, albeit at a slower pace due to infrastructural and regulatory challenges. Limited access to advanced IT infrastructure, a shortage of skilled personnel, and varying data privacy regulations pose significant hurdles to widespread implementation. However, localized demand from sectors such as mining, oil & gas, and agriculture is creating niche opportunities for dataset versioning tools tailored to specific operational environments. Policymakers in these regions are increasingly recognizing the potential of robotics and AI, introducing pilot programs and incentives to stimulate market growth. As awareness grows and digital infrastructure improves, these regions are expected to contribute more significantly to the global market in the latter part of the forecast period.

Report Scope

This dataset contains detailed specifications and official launch prices of various mobile phone models from different companies. It provides insights into smartphone hardware, pricing trends, and brand competitiveness across multiple countries. The dataset includes key features such as RAM, camera specifications, battery capacity, processor details, and screen size.

One important aspect of this dataset is the pricing information. The recorded prices represent the official launch prices of the mobile phones at the time they were first introduced in the market. Prices vary based on the country and the launch period, meaning older models reflect their original launch prices, while newer models include their most recent launch prices. This makes the dataset valuable for studying price trends over time and comparing smartphone affordability across different regions.

Features:

• Company Name: The brand or manufacturer of the mobile phone.
• Model Name: The specific model of the smartphone.
• Mobile Weight: The weight of the mobile phone (in grams).
• RAM: The amount of Random Access Memory (RAM) in the device (in GB).
• Front Camera: The resolution of the front (selfie) camera (in MP).
• Back Camera: The resolution of the primary rear camera (in MP).
• Processor: The chipset or processor used in the device.
• Battery Capacity: The battery size of the smartphone (in mAh).
• Screen Size: The display size of the smartphone (in inches).
• Launched Price: (Pakistan, India, China, USA, Dubai): The official launch price of the mobile in the respective country at the time of its release. Prices vary based on the year the mobile was launched.
• Launched Year: The year the mobile phone was officially launched.

The population share with mobile internet access in Canada was forecast to continuously increase between 2024 and 2029 by in total 1.5 percentage points. After the fifteenth consecutive increasing year, the mobile internet penetration is estimated to reach 92.51 percent and therefore a new peak in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the population share with mobile internet access in countries like United States and Mexico.

Time Series Database for Financial Services Market Outlook

As per our latest research, the global Time Series Database for Financial Services market size in 2024 reached USD 1.85 billion, demonstrating robust growth driven by the increasing adoption of real-time analytics and data-driven decision-making in the financial sector. The market is expected to expand at a CAGR of 13.2% from 2025 to 2033, reaching a forecasted value of USD 5.44 billion by 2033. The primary growth factor for this market is the escalating volume of financial transactions and the growing need for high-frequency data analysis, which is crucial for risk management, fraud detection, and algorithmic trading across global financial institutions.

One of the most significant growth drivers for the Time Series Database for Financial Services market is the exponential rise in digital transactions and the proliferation of fintech solutions. Financial institutions are increasingly leveraging time series databases to process and analyze vast streams of transactional data in real time. This capability is essential for supporting complex applications such as algorithmic trading, which relies on millisecond-level data precision to execute trades and manage portfolios efficiently. The surge in mobile banking, online payments, and digital wallets has further amplified the demand for scalable and high-performance databases that can handle the velocity, volume, and variety of financial data generated every second. As financial services become more digitized, the need for robust data infrastructure continues to intensify, propelling the market forward.

Another critical factor fueling market growth is the regulatory environment and the increasing emphasis on compliance and risk management. Financial institutions are under mounting pressure to comply with stringent regulations imposed by global authorities, which necessitate comprehensive data tracking, auditing, and reporting capabilities. Time series databases offer an efficient way to store and retrieve historical data, making it easier for banks, investment firms, and insurance companies to demonstrate compliance and quickly respond to regulatory inquiries. Moreover, the integration of advanced analytics and artificial intelligence with time series databases enables organizations to detect anomalies, predict risks, and automate compliance workflows, thereby reducing operational costs and mitigating potential penalties.

Technological advancements and the rise of cloud computing are also pivotal in shaping the growth trajectory of the Time Series Database for Financial Services market. Cloud-based deployment models have democratized access to high-performance databases, enabling even small and medium-sized enterprises to leverage sophisticated data management capabilities without significant upfront investments. The scalability, flexibility, and cost-efficiency offered by cloud solutions are attracting a diverse range of financial service providers, from traditional banks to innovative fintech startups. Furthermore, the integration of time series databases with big data platforms and machine learning tools is unlocking new opportunities for real-time analytics, personalized financial services, and predictive modeling, all of which contribute to the sustained expansion of the market.

From a regional perspective, North America continues to dominate the global Time Series Database for Financial Services market, accounting for the largest revenue share in 2024. This leadership position is attributed to the presence of major financial hubs, advanced IT infrastructure, and early adoption of cutting-edge technologies by leading banks and investment firms. However, the Asia Pacific region is emerging as the fastest-growing market, driven by rapid digital transformation, increasing investments in fintech, and the rising adoption of cloud-based solutions in countries such as China, India, and Singapore. Europe is also witnessing substantial growth, supported by stringent regulatory frameworks and the increasing focus on data-driven financial services. Latin America and the Middle East & Africa are gradually catching up, with financial institutions in these regions investing in modern database solutions to enhance operational efficiency and customer experience.

In the evolving landscape of financial services, <a href="https://growthmarketreports.com/report/managed-temporal-services-market" target="_blank&

Mobile Robot Benchmark Datasets Market Outlook

According to our latest research, the global Mobile Robot Benchmark Datasets market size reached USD 1.12 billion in 2024, driven by the rapid adoption of autonomous systems across various industries and the increasing need for standardized evaluation tools. The market is projected to grow at a robust CAGR of 18.7% from 2025 to 2033, with the market size expected to reach USD 5.89 billion by 2033. Key growth factors include the expanding deployment of mobile robots in logistics, healthcare, and defense, as well as the rising demand for high-quality, diverse datasets to train and benchmark advanced robotic algorithms.

One of the primary drivers fueling the growth of the Mobile Robot Benchmark Datasets market is the surging adoption of autonomous mobile robots (AMRs) across various industrial and commercial sectors. Industries such as logistics, warehousing, and manufacturing are increasingly relying on AMRs to optimize operational efficiency, reduce labor costs, and enhance workplace safety. The deployment of these robots necessitates robust datasets for training, validation, and benchmarking of navigation, perception, and decision-making algorithms. As the complexity of robotic systems grows, so does the need for comprehensive and diverse datasets that can simulate real-world challenges, ensuring that robots can operate reliably in dynamic and unpredictable environments. This trend is further accelerated by the proliferation of Industry 4.0 initiatives and the integration of artificial intelligence (AI) and machine learning (ML) in robotic platforms, making benchmark datasets indispensable for innovation and quality assurance.

Another significant growth factor is the increasing collaboration between academia, research institutions, and industry players to develop standardized and open-source benchmark datasets for mobile robots. These collaborations are crucial for establishing common evaluation metrics, fostering transparency, and accelerating the pace of technological advancements. The availability of high-quality datasets enables researchers and developers to benchmark their algorithms against standardized scenarios, facilitating objective performance comparisons and driving continuous improvement. Moreover, government agencies and international bodies are supporting initiatives aimed at creating publicly accessible datasets to democratize research and development in robotics. This collaborative ecosystem not only enhances the quality and diversity of available datasets but also promotes interoperability and cross-industry adoption of mobile robotics solutions.

The growing emphasis on safety, reliability, and regulatory compliance in autonomous systems is also propelling the demand for benchmark datasets in the mobile robotics sector. Regulatory authorities are increasingly mandating rigorous testing and validation of autonomous systems before their deployment in public and safety-critical environments. Benchmark datasets play a pivotal role in ensuring that mobile robots meet stringent safety and performance standards by providing standardized scenarios for testing navigation, obstacle avoidance, and decision-making algorithms. This regulatory push, coupled with the rising expectations of end-users for seamless and error-free robotic operations, is compelling manufacturers and solution providers to invest heavily in comprehensive benchmarking tools and datasets, thereby driving market growth.

From a regional perspective, North America currently dominates the Mobile Robot Benchmark Datasets market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The presence of leading technology companies, advanced research institutions, and a robust startup ecosystem in the United States and Canada has positioned North America as a hub for innovation in mobile robotics and AI. Europe is witnessing significant growth, driven by strong government support for robotics research and the increasing adoption of automation in manufacturing and logistics. Meanwhile, Asia Pacific is emerging as the fastest-growing region, fueled by rapid industrialization, urbanization, and substantial investments in AI and robotics infrastructure in countries such as China, Japan, and South Korea. The regional dynamics are further influenced by the availability of skilled talent, supportive regulatory frameworks, and the pace of digital transformation across key industries.

Dataset Type Analysis

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Mobile Robot Dataset Versioning Market Outlook

According to our latest research, the global mobile robot dataset versioning market size reached USD 412 million in 2024, and is expected to grow at a robust CAGR of 16.2% during the forecast period, reaching approximately USD 1.15 billion by 2033. This growth is primarily driven by the increasing adoption of mobile robots across diverse industries and the critical need for robust dataset management solutions to ensure accurate training, deployment, and continuous improvement of autonomous systems. The proliferation of AI-powered robots and rapid advancements in machine learning algorithms are further fueling the demand for sophisticated dataset versioning platforms, enabling organizations to manage, track, and audit data changes efficiently.

One of the most significant growth factors for the mobile robot dataset versioning market is the exponential increase in the deployment of autonomous robots in industries such as logistics, manufacturing, and healthcare. As these robots become more sophisticated, the datasets required for their training and operation also become larger and more complex. Accurate dataset versioning ensures that every iteration of training and operational data is meticulously tracked, which is essential for regulatory compliance, quality assurance, and continuous performance improvement. Companies are increasingly recognizing the role of dataset versioning in minimizing errors, reducing operational downtime, and accelerating the development lifecycle of autonomous systems. The ability to roll back to previous dataset versions or audit changes has become a vital requirement, especially in safety-critical applications.

Another key driver is the rise of collaborative robotics and multi-robot systems, which generate vast amounts of heterogeneous data from diverse sources such as sensors, cameras, and LIDAR. Managing these datasets in real time, especially when updates and modifications are frequent, necessitates advanced versioning solutions that can handle distributed environments. The growing emphasis on data quality, integrity, and traceability is pushing organizations to invest in specialized software and services that provide granular control over dataset modifications. Furthermore, the integration of cloud-based platforms with dataset versioning capabilities allows for seamless collaboration among geographically dispersed teams, thus enhancing productivity and innovation in robot development and deployment.

The market is also benefiting from increased research activities in academia and industry, focusing on improving the accuracy and efficiency of autonomous navigation, mapping, and object recognition. These research initiatives generate vast volumes of experimental data that must be versioned and managed efficiently to support reproducibility and peer collaboration. The growing adoption of open-source frameworks and standardized dataset management practices is further catalyzing market growth. At the same time, regulatory requirements for data transparency and auditability in sectors like healthcare and defense are compelling organizations to adopt advanced dataset versioning solutions, ensuring that all data used in robot training and operation is properly documented and traceable.

From a regional perspective, North America and Europe currently dominate the mobile robot dataset versioning market, driven by robust investments in robotics research, a strong presence of technology vendors, and early adoption of advanced data management solutions. However, the Asia Pacific region is emerging as the fastest-growing market, propelled by rapid industrialization, increased automation in manufacturing and logistics, and significant government initiatives supporting AI and robotics innovation. The Middle East & Africa and Latin America are also witnessing steady growth, albeit from a smaller base, as organizations in these regions increasingly recognize the benefits of dataset versioning in optimizing robot performance and ensuring data compliance. The global landscape is thus characterized by a dynamic interplay of technological advancement, regulatory evolution, and industry-specific adoption patterns.

Component Analysis

The component segment of the mobile robot dataset versioning market is divided into software, hardware, and services, each playing a distinct role in the ecosystem. Software solutions form the backb

Golden Dataset Curation for LLMs Market Outlook

According to our latest research, the Global Golden Dataset Curation for LLMs market size was valued at $1.2 billion in 2024 and is projected to reach $8.7 billion by 2033, expanding at a CAGR of 24.8% during 2024–2033. This remarkable growth trajectory is primarily driven by the increasing demand for high-quality, bias-mitigated, and diverse datasets essential for training and evaluating large language models (LLMs) across industries. As generative AI applications proliferate, organizations are recognizing the strategic importance of curating "golden datasets"—carefully selected, annotated, and validated data collections that ensure robust model performance, regulatory compliance, and ethical AI outcomes. The accelerating adoption of AI-powered solutions in sectors such as healthcare, finance, and government, coupled with ongoing advances in data curation technologies, are further fueling the expansion of the Golden Dataset Curation for LLMs market globally.

Regional Outlook

North America currently commands the largest share of the Golden Dataset Curation for LLMs market, accounting for approximately 38% of the global revenue in 2024. This dominance is underpinned by the region’s mature artificial intelligence ecosystem, the presence of leading technology companies, and robust investments in R&D. The United States, in particular, boasts a high concentration of AI expertise, advanced data infrastructure, and a strong regulatory framework that supports ethical data curation. Furthermore, North America’s proactive adoption of generative AI across industries such as healthcare, BFSI, and government has spurred demand for meticulously curated datasets to drive innovation and ensure compliance with evolving data privacy standards. The region’s leadership in launching open-source initiatives and public-private partnerships for AI research further cements its preeminent position in the global market.

Asia Pacific is emerging as the fastest-growing region, projected to register a robust CAGR of 28.4% from 2024 to 2033. The region’s rapid market expansion is propelled by exponential growth in digital transformation initiatives, increasing AI investments, and supportive government policies aimed at fostering indigenous AI capabilities. Countries such as China, India, and South Korea are making significant strides in AI research, with a particular emphasis on local language and multimodal dataset curation to cater to diverse populations. The proliferation of startups and technology incubators, coupled with strategic collaborations between academia and industry, is accelerating the development and adoption of golden datasets. Additionally, the region’s burgeoning internet user base and mobile-first economies are generating vast volumes of data, providing fertile ground for dataset curation innovation.

Emerging economies in Latin America, the Middle East, and Africa are witnessing gradual but promising adoption of Golden Dataset Curation for LLMs. While market penetration remains lower compared to developed regions, localized demand for AI-driven solutions in sectors such as public health, education, and government services is spurring investment in dataset curation capabilities. However, challenges such as limited access to high-quality data, fragmented regulatory environments, and a shortage of specialized talent are impeding rapid growth. Despite these hurdles, targeted policy reforms, international collaborations, and capacity-building initiatives are laying the groundwork for future market expansion, particularly as governments recognize the strategic value of AI and data sovereignty.

Report Scope

NoSQL Database Market size was valued at USD 6.47 Billion in 2024 and is expected to reach USD 44.66 Billion by 2032, growing at a CAGR of 30.14% from 2026 to 2032.Global NoSQL Database Market DriversExponential Growth of Big Data and IoT: The explosion of Big Data and Internet of Things (IoT) applications is a primary catalyst for NoSQL adoption, requiring database solutions that can ingest and process colossal volumes of unstructured and semi-structured data from diverse sources like sensors, social media, and web logs. Unlike rigid relational systems, Increasing Demand for Real-Time Web and Mobile Applications: The surging demand for real-time web and mobile applications is significantly fueling the NoSQL market, as these modern applications require sub-millisecond latency and exceptionally high throughput to deliver a seamless user experience. NoSQL database types, particularly key-value stores and document databases, are architecturally optimized for rapid read/write operations and horizontal scaling,.

According to Cognitive Market Research, the global cloud database and DBaaS marketsize was USD 21.9 billion in 2024 and will increase at a compound annual growth rate (CAGR) of 21.6% from 2024 to 2031. Market Dynamics of Cloud Database and DBaaS Market Key Drivers for Cloud Database and DBaaS Market Mobile and IoT Adoption - The rise of mobile and IoT technologies fuels demand for cloud databases and DBaaS solutions. Data generation surges as mobile usage skyrockets and IoT devices flourish, necessitating scalable, accessible storage options. Cloud databases offer flexibility and scalability to accommodate these dynamic workloads while enabling seamless integration with mobile and IoT applications. The shift towards digital transformation initiatives also amplifies the need for agile, cloud-native database solutions to support modernization efforts across industries. Automated administration reduces operational complexity, which drives the cloud database and DBaaS market's expansion in the years ahead. Key Restraints for Cloud Database and DBaaS Market Compatibility issues with existing systems hinder the adoption of the cloud database and DBaaS in the industry. The market also faces significant difficulties related to data migration challenges that hinder adoption and scalability.. Introduction of the Cloud Database and DBaaS Market Cloud databases and Database-as-a-Service (DBaaS) offer scalable and managed storage solutions where data is hosted and accessed over the internet. Market drivers for these services include the imperative for scalability to accommodate growing data volumes, cost efficiencies achieved through a shift from capital to operational expenditure, enhanced accessibility enabling collaboration and innovation from any location, heightened demand for robust security features to address data privacy concerns, simplified management through automated administration, and elasticity to handle fluctuating workloads seamlessly. These drivers collectively address modern business needs for flexibility, cost-effectiveness, security, and performance. As organizations increasingly depend on data as a strategic asset, cloud databases, and DBaaS solutions provide the agility and efficiency required to meet evolving demands while leveraging the benefits of cloud computing infrastructure.

Diluted-Average-Shares Time Series for Nordea Bank Abp. Nordea Bank Abp offers banking products and services for individuals, families, and businesses in Sweden, Finland, Norway, Denmark, and internationally. It operates through Personal Banking, Business Banking, Large Corporates & Institutions, and Asset & Wealth Management segments. The company provides various financial services to customers through mobile banking, over the phone, online meetings, and branch offices. It also offers payments, cash management, cards, working capital management, and cards and finance solutions. In addition, the company provides financing, payment, investment banking, capital market products, and securities services; and investment, savings, and risk management solutions. Further, it offers savings products and asset management, including investment funds, discretionary management, portfolio advice, and equity trading and pension accounts; and asset-based financing through leasing, hire purchase, factoring, and sales to finance partners, such as dealers, vendors and retailers, as well as life insurance and pension products and services. Nordea Bank Abp was founded in 1820 and is headquartered in Helsinki, Finland.

The mobile phone dataset comprises a comprehensive collection of mobile devices, each with detailed information on prices and features. The dataset is organized in a structured format for easy analysis. Here is an overview of the key components:

Mobile Phone Models: The dataset includes a list of unique mobile phone models, each identified by a distinct identifier or name.

Price Information:

Average Price: The average price of the mobile phones in the dataset is [average price]. Price Range: The prices range from [minimum price] to [maximum price]. Features:

Display: Information on display size, resolution, and type (e.g., OLED, LCD). Processor: Details about the chipset and processing power. Camera: Specifications for front and rear cameras, including megapixels and additional features. Storage: Available internal storage capacities (in GB or TB). Battery: Battery capacity and type. Operating System: The mobile operating system (e.g., iOS, Android) and version. Connectivity: Details on network support (e.g., 4G, 5G) and other connectivity options (e.g., Bluetooth, Wi-Fi). Additional Features: Any special functionalities or hardware features unique to each mobile. Brand Information:

The dataset may contain information about the brand or manufacturer of each mobile phone. Release Date: Date of release or launch for each mobile phone model.

Availability: Availability status (e.g., current, discontinued) of each mobile phone model.

User Ratings/Reviews (if available): Any user-generated ratings or reviews associated with the mobile phones.

Market Segment/Category (optional): Classification of mobile phones into categories like budget, mid-range, or flagship.

Market Trends (if tracked): Trends or insights related to mobile phone sales, popularity, or market share over time.

Context

It is no secret that mobile devices are increasingly taking over the market at the expense of stationary equipment and many forgotten tablets. Trends change over time and the data collected helps us understand them. So let's look at the share of these three sections in the most populous country in the world, which is India.

Content

The database saved in .csv form contains 4 columns. The first column contains the date (YYYY-MM) from the measurement period. Each subsequent column contains the percentage of market share in mobile, desktop and tablet markets, given as a percentage, rounded to 2 decimal places (if the share is less than 0.5%, the value 0 remains, even though it may constitute a very small percentage of the share). We have a total of 180 rows, i.e. full 15 years of data for each month.

Source

The database comes from the statcounter website and is available under the CC BY-SA 3.0 license, which allows you to copy, use and distribute the data also for commercial purposes after citing the source.

Photo by Andrew Neel on Unsplash