The Registry of Open Data on AWS contains publicly available datasets that are available for access from AWS resources. Note that datasets in this registry are available via AWS resources, but they are not provided by AWS; these datasets are owned and maintained by a variety of government organizations, researchers, businesses, and individuals. This dataset contains derived forms of the data in https://github.com/awslabs/open-data-registry that have been transformed for ease of use with machine interfaces. Currently, only the ndjson form of the registry is populated here.

The Data Exchange Platform Services Marketsize was valued at USD 1.3 billion in 2023 and is projected to reach USD 7.5 billion by 2032, exhibiting a CAGR of 19.15 % during the forecast period. Recent developments include: November 2019: Amazon Web Services (AWS) partnered with Deloitte to help customers securely find, subscribe to, and use third-party data in the cloud using AWS Data Exchange, a new service that can help address unique healthcare issues. March 2020: Google Cloud Platform (GCP) launched Anthos, a new platform that enables businesses to run their applications across multiple clouds and on-premises environments. Anthos includes a data exchange feature that allows businesses to share data between their applications, regardless of where they are deployed.. Key drivers for this market are: Increasing Adoption of Cloud-based Managed Services to Drive Market Growth. Potential restraints include: Misuse of Virtual Currency and Security Attacks Confines the Adoption of Cryptocurrencies. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

A multidisciplinary repository of public data sets such as the Human Genome and US Census data that can be seamlessly integrated into AWS cloud-based applications. AWS is hosting the public data sets at no charge for the community. Anyone can access these data sets from their Amazon Elastic Compute Cloud (Amazon EC2) instances and start computing on the data within minutes. Users can also leverage the entire AWS ecosystem and easily collaborate with other AWS users. If you have a public domain or non-proprietary data set that you think is useful and interesting to the AWS community, please submit a request and the AWS team will review your submission and get back to you. Typically the data sets in the repository are between 1 GB to 1 TB in size (based on the Amazon EBS volume limit), but they can work with you to host larger data sets as well. You must have the right to make the data freely available.

The Sentinel-2 mission is a land monitoring constellation of two satellites that provide high resolution optical imagery and provide continuity for the current SPOT and Landsat missions. The mission provides a global coverage of the Earth's land surface every 5 days, making the data of great use in on-going studies. L1C data are available from June 2015 globally. L2A data are available from November 2016 over Europe region and globally since January 2017.

Automated Weather Station and AWS-like networks are the primary source of surface-level meteorological data in remote polar regions. These networks have developed organically and independently, and deliver data to researchers in idiosyncratic ASCII formats that hinder automated processing and intercomparison among networks. Moreover, station tilt causes significant biases in polar AWS measurements of radiation and wind direction. Researchers, network operators, and data centers would benefit from AWS-like data in a common format, amenable to automated analysis, and adjusted for known biases. This project addresses these needs by developing a scientific software workflow called "Justified AWS" (JAWS) to ingest Level 2 (L2) data in the multiple formats now distributed, harmonize it into a common format, and deliver value-added Level 3 (L3) output suitable for distribution by the network operator, analysis by the researcher, and curation by the data center. Polar climate researchers currently face daunting problems including how to easily: 1. Automate analysis (subsetting, statistics, unit conversion) of AWS-like L2 ASCII data. 2. Combine or intercompare data and data quality from among unharmonized L2 datasets. 3. Adjust L2 data for biases such as AWS tilt angle and direction. JAWS addresses these common issues by harmonizing AWS L2 data into a common format, and applying accepted methods to quantify quality and estimate biases. Specifically, JAWS enables users and network operators to 1. Convert L2 data (usually ASCII tables) into a netCDF-based L3 format compliant with metadata conventions (Climate-Forecast and ACDD) that promote automated discovery and analysis. 2. Include value-added L3 features like the Retrospective, Iterative, Geometry-Based (RIGB) tilt angle and direction corrections, solar angles, and standardized quality flags. 3. Provide a scriptable API to extend the initial L2-to-L3 conversion to newer AWS-like networks and instruments. Polar AWS network experts and NSIDC DAAC personnel, each with decades of experience, will help guide and deliberate the L3 conventions implemented in Stages 2-3. The project will start on July 1, 2017 at entry Technology Readiness Level 3 and will exit on June 30, 2019 at TRL 6. JAWS is now a heterogeneous collection of scripts and methods developed and validated at UCI over the past 15 years. At exit, JAWS will comprise three modular stages written in or wrapped by Python, installable by Conda: Stage 1 ingests and translates L2 data into netCDF. Stage 2 annotates the netCDF with CF and ACDD metadata. Stage 3 derives value-added scientific and quality information. The labor-intensive tasks include turning our heterogeneous workflow into a robust, standards-compliant, extensible workflow with an API based on best practices of modern scientific information systems and services. Implementation of Stages 1-2 may be straightforward though tedious due to the menagerie of L2 formats, instruments, and assumptions. The RIGB component of Stage 3 requires ongoing assimilation of ancillary NASA data (CERES, AIRS) and use of automated data transfer protocols (DAP, THREDDS). The immediate target recipient elements are polar AWS network managers, users, and data distributors. L2 borehole data suffers from similar interoperability issues, as does non-polar AWS data. Hence our L3 format will be extensible to global AWS and permafrost networks. JAWS will increase in situ data accessibility and utility, and enable new derived products (both are AIST goals). The PI is a long-standing researcher, open source software developer, and educator who understands obstacles to harmonizing disparate datasets with NASA interoperability recommendations. Our team participates in relevant geoscience communities, including ESDS working groups, ESIP, AGU, and EarthCube.

The AWS Public Blockchain Data initiative provides free access to blockchain datasets through collaboration with data providers. The data is optimized for analytics by being transformed into compressed Parquet files, partitioned by date for efficient querying.

Datasets

Blockchain dataset - Maintained by - Path:
- Bitcoin - AWS - s3://aws-public-blockchain/v1.0/btc/
- Ethereum - AWS - s3://aws-public-blockchain/v1.0/eth/
- Arbitrum - SonarX - s3://aws-public-blockchain/v1.1/sonarx/arbitrum/
- Aptos - SonarX - s3://aws-public-blockchain/v1.1/sonarx/aptos/
- Base - SonarX - s3://aws-public-blockchain/v1.1/sonarx/base/
- Provenance - SonarX - s3://aws-public-blockchain/v1.1/sonarx/provenance/
- XRP Ledger - SonarX - s3://aws-public-blockchain/v1.1/sonarx/xrp/
- Stellar(XDR files) - Stellar - s3://aws-public-blockchain/v1.1/stellar/
- The Open Network (TON) - TON - s3://aws-public-blockchain/v1.1/ton/
- Cronos - Cronos - s3://aws-public-blockchain/v1.1/cronos/

Become a Data Provider

We welcome additional blockchain data providers to join this initiative. If you're interested in contributing datasets to the AWS Public Blockchain Data program, please contact our team at aws-public-blockchain@amazon.com.

In the fourth quarter of 2024, the most popular vendor in the cloud infrastructure services market, Amazon Web Services (AWS), controlled ** percent of the entire market. Microsoft Azure takes second place with ** percent market share, followed by Google Cloud with ** percent market share. Together, these three cloud vendors account for ** percent of total spend in the fourth quarter of 2024. Organizations use cloud services from these vendors for machine learning, data analytics, cloud native development, application migration, and other services. AWS Services Amazon Web Services is used by many organizations because it offers a wide variety of services and products to its customers that improve business agility while being secure and reliable. One of AWS’s most used services is Amazon EC2, which lets customers create virtual machines for their strategic projects while spending less time on maintaining servers. Another important service is Amazon Simple Storage Service (S3), which offers a secure file storage service. In addition, Amazon also offers security, website infrastructure management, and identity and access management solutions. Cloud infrastructure services Vendors offering cloud services to a global customer base do so through different types of cloud computing, which include infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Further, there are different cloud computing deployment models available for customers, namely private cloud and public cloud, as well as community cloud and hybrid cloud. A cloud deployment model is defined based on the location where the deployment resides, and who has access to and control over the infrastructure.

The NEX-GDDP-CMIP6 dataset is comprised of global downscaled climate scenarios derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 6 (CMIP6) and across two of the four "Tier 1" greenhouse gas emissions scenarios known as Shared Socioeconomic Pathways (SSPs). The CMIP6 GCM runs were developed in support of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR6). This dataset includes downscaled projections from ScenarioMIP model runs for which daily scenarios were produced and distributed through the Earth System Grid Federation. The purpose of this dataset is to provide a set of global, high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions.

The global data catalog market is experiencing steady growth, driven by the increasing volume and complexity of enterprise data. As organizations face the challenge of managing multiple data sources and ensuring data quality and governance, the adoption of data catalogs has become increasingly important. According to market research, the total value of the market in 2025 was approximately $2.61 billion, with a projected CAGR of 2.50% from 2025 to 2033. This growth is primarily attributed to the growing need for data-driven decision-making and the proliferation of big data and artificial intelligence (AI) technologies. Key industry trends indicate a growing emphasis on cloud-based data catalog solutions, as well as the integration of AI and machine learning (ML) capabilities. These technologies enhance the automation and efficiency of data cataloging processes, while providing advanced features such as data lineage tracking and data quality monitoring. Furthermore, the convergence of data catalog solutions with other enterprise applications, such as data governance and data analytics platforms, creates opportunities for comprehensive data management and improved data utilization. The competitive landscape is characterized by a mix of established vendors and emerging players, with companies such as Tamr Inc, Collibra NV, TIBCO Software Inc, and IBM Corporation holding significant market share. Ongoing innovations and strategic acquisitions are shaping the market dynamics, as vendors strive to differentiate their offerings and meet evolving customer requirements. The global data catalog market size was valued at USD 2.0 billion in 2022 and is expected to expand at a compound annual growth rate (CAGR) of 24.3% from 2023 to 2030, reaching USD 12.0 billion by 2030. Recent developments include: November 2022 - Amazon EMR customers can now use AWS Glue Data Catalog from their streaming and batch SQL workflows on Flink. The AWS Glue Data Catalog is an Apache Hive metastore-compatible catalog. With this release, Companies can directly run Flink SQL queries against the tables stored in the Data Catalog., September 2022 - Syniti, a global leader in enterprise data management, updated new data quality and catalog capabilities available in its industry-leading Syniti Knowledge Platform, building on the enhancements in data migration and data matching added earlier this year. The Syniti Knowledge Platform now includes data quality, catalog, matching, replication, migration, and governance, all available under one login in a single cloud solution. It provides users with a complete and unified data management platform enabling them to deliver faster and better business outcomes with data they can trust., August 2022 - Oracle Cloud Infrastructure collaborated with Anaconda, the world's most recognized data science platform provider. By permitting and integrating the latter company's repository throughout OCI Machine Learning and Artificial Intelligence services, the collaboration aimed to give safe, open-source Python and R tools and packages.. Key drivers for this market are: Growing adoption of Cloud Based Solutions, Solutions Segment is Expected to Hold a Larger Market Size. Potential restraints include: Lack of Standardization and Security Concerns. Notable trends are: Solutions Segment is Expected to Hold a Larger Market Size.

The Data Pipeline Marketsize was valued at USD 6.81 USD billion in 2023 and is projected to reach USD 28.03 USD billion by 2032, exhibiting a CAGR of 22.4 % during the forecast period. Recent developments include: In 2021, IBM acquired Databand AI, a provider of data observability and quality monitoring solutions. This acquisition will help IBM to strengthen its position in the data pipeline market. In 2020, Amazon Web Services (AWS) launched Amazon Data Pipeline, a fully managed data pipeline service that makes it easy to build, run, and monitor data pipelines. This service will help AWS to gain market share in the data pipeline market.. Key drivers for this market are: Increased Use of Advanced Data Pipeline Tools for Cloud Flexibility among Organizations to Bolster Market Growth. Potential restraints include: Lack of Access to Data in Business Processes May Impede Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

Amazon (AMZN) Stock Price Time-Series Dataset: May 2012 - November 2012

Dataset Overview

This dataset provides a detailed, intraday view of Amazon's stock (AMZN) price movements from May 21, 2012, to November 14, 2012. Meticulously compiled, it offers a granular perspective on market dynamics, enabling robust quantitative analysis and modeling.

Content

The dataset encompasses the following key financial metrics for each trading day:

• Date: The specific date of the trading session.
• Open: The initial price at the commencement of trading.
• High: The maximum price attained during the trading day.
• Low: The minimum price recorded during the trading day.
• Close: The final trading price at the market's close.
• Adj Close: The closing price adjusted for corporate actions like dividends and stock splits, providing a true return on investment.
• Volume: The number of shares exchanged throughout the trading day, indicating market activity and liquidity.

Intended Use Cases

This dataset is tailored for sophisticated financial analysis, model development, and academic research. Potential applications include:

• Algorithmic Trading Strategy Development: Design and back-test trading algorithms using historical price movements and volume data.
• Volatility Modeling: Analyze and forecast stock price volatility using time-series analysis techniques (e.g., GARCH models).
• Financial Forecasting: Implement machine learning models to predict future stock prices based on historical patterns.
• Event Study Analysis: Examine the impact of specific events or news announcements on Amazon's stock price.
• Risk Management: Evaluate potential risks associated with investing in Amazon stock during this period.
• Academic Research: Conduct studies on market efficiency, price discovery, and the impact of market microstructure on stock behavior.

Data Considerations

• Time Zone: Data is timestamped with Eastern Time (ET).
• Data Cleaning: The dataset has been verified for accuracy, but users are encouraged to perform their own data quality checks.

Contect info:

You can contect me for more data sets if you want any type of data to scrape

-E_mail

-Linkdin

-Kaggle

-X

-Github

The NASA Earth Exchange (NEX) Downscaled Climate Projections (NEX-DCP30) dataset is comprised of downscaled climate scenarios for the conterminous United States that are derived from the General Circulation Model (GCM) runs conducted under the Coupled Model Intercomparison Project Phase 5 (CMIP5) [Taylor et al. 2012] and across the four greenhouse gas emissions scenarios known as Representative Concentration Pathways (RCPs) [Meinshausen et al. 2011] developed for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5). The dataset includes downscaled projections from 33 models, as well as ensemble statistics calculated for each RCP from all model runs available. The purpose of these datasets is to provide a set of high resolution, bias-corrected climate change projections that can be used to evaluate climate change impacts on processes that are sensitive to finer-scale climate gradients and the effects of local topography on climate conditions. Each of the climate projections includes monthly averaged maximum temperature, minimum temperature, and precipitation for the periods from 1950 through 2005 (Retrospective Run) and from 2006 to 2099 (Prospective Run).

The size of the Data Lakes Market was valued at USD XX Million in 2023 and is projected to reach USD XXX Million by 2032, with an expected CAGR of 22.40% during the forecast period. Recent developments include: December 2022: Atos announced the development of a new solution in collaboration with AWS that allows clients to expedite and properly monitor company key performance indicators (KPIs) by offering simple access to non-SAP and SAP data silos. "Atos' AWS Data Lake Accelerator for SAP" is an innovative solution that delivers enterprise-wide and self-service reporting for significant insights into daily changes that rapidly impact decisions to drive the bottom line., November 2022: Amazon Web Services (AWS) announced the launch of Amazon Security Lake. This new cybersecurity solution automatically centralizes safety data from on-premises and cloud sources into a purpose-built data lake in a user's AWS account.. Key drivers for this market are: Proliferation of Data due to the Adoption of IoT, Need for Advanced Analytic Capabilities. Potential restraints include: Slow Onboarding and Data Integration of Data Lakes. Notable trends are: BFSI End-user Vertical Segment is Expected to Hold Significant Market Share.

The size of the Data Catalog Market was valued at USD 37.58 billion in 2023 and is projected to reach USD 172.58 billion by 2032, with an expected CAGR of 24.33% during the forecast period. Recent developments include: Amazon EMR customers can now use AWS Glue Data Catalog from their streaming and batch SQL workflows on Flink. AWS Glue Data Catalog is a catalog that works with Apache Hive metastore. Companies may now execute Flink SQL queries directly on the tables that are kept in the Data Catalog., August 2022, Oracle Cloud Infrastructure announced its collaboration with Anaconda, the world's most recognized data science platform provider. The agreement aims to provide safe, open-source Python and R tools and packages by allowing and integrating the latter company's repository throughout OCI Machine Learning and Artificial Intelligence services.. Potential restraints include: PREVALENCE OF ALTERNATIVE PAYMENT GATEWAYS MAY IMPEDE GROWTH PROSPECTS 31, LIMITED TRANSACTION SIZES AND LIMITED MERCHANT ADOPTION 32.

The Data Catalog Marketsize was valued at USD 878.8 USD million in 2023 and is projected to reach USD 2749.95 USD million by 2032, exhibiting a CAGR of 17.7 % during the forecast period. Recent developments include: February 2024 – Collibra launched Collibra AI Governance, built on their Data Intelligence Platform, enabling organizations to deliver trusted AI effectively through the use of Collibra Data Catalog. It aided teams in collaborating for compliance, improved model performance, reduced risk, and led to faster production timelines., September 2023 – AWS Lake Formation launched a Hybrid Access Module for the AWS Glue Data Catalog, allowing users to selectively enable Lake Formation for tables and databases without interrupting existing users or workloads. This feature provided flexibility and an integral path for enabling Lake Formation, reducing the need for coordination among owners and consumers., July 2023 – Teradata acquired Stemma Technologies to enhance its analytics capabilities, particularly in data discovery and delivery. Stemma’s automated data catalog bolstered Teradata’s offerings, aiming to improve user experience and accelerate ML and AI analytics growth., June 2023 – Acryl Data secured USD 21 million in Series A funding led by 8VC to enhance its open-source data catalog platform. This investment enhanced their cloud offerings and expanded their vision towards a data control plane., May 2023 – data.world launched its new Data Catalog Platform, integrating generative AI bots to enhance data discovery. With over 2 million users, the platform aimed to make data discovery and knowledge unlocking accessible to users of all expertise levels., February 2023 – data.world, a data governance platform, launched the first AI Lab for the data catalog industry. This Artificial Intelligence (AI) Lab would be important in bringing partners and customers together to enhance data team productivity using AI technology., November 2022 – Amazon Web Services (AWS) launched DataZone, a new machine learning-based data management service to help enterprises catalog, share, govern, and discover their data quickly.. Key drivers for this market are: Exponential Growth of Data Volume and Data Analytics to Fuel Market Growth. Potential restraints include: High Initial Deployment Cost and Privacy Concerns to Hinder Market Growth. Notable trends are: Growing Adoption of AI and Automation Technologies to Amplify Market Growth.

Dataset Description This dataset contains historical stock price data across multiple timeframes, ranging from intraday to higher timeframes. The available timeframes include:

1-minute (1m) 5-minute (5m) 30-minute (30m) 60-minute (1h) 240-minute (4h) Daily (1D) Weekly (1W) Monthly (1M)

Each dataset file represents price movements at a specific timeframe, enabling traders and analysts to perform technical analysis across different granularities.

Columns - datetime: The timestamp or date of the recorded price data. - open: The opening price at the beginning of the timeframe. - high: The highest price reached within the timeframe. - low: The lowest price reached within the timeframe. - close: The closing price at the end of the timeframe. - % change: The percentage change in price from the previous timeframe, indicating the rate of price movement.

Exchange Information The dataset is sourced from the IC Market exchange, ensuring reliable and up-to-date market data. https://in.tradingview.com/broker/ICmarkets/

Time Period Covered The dataset spans from the inception of the company to 2025, covering complete historical stock price data.

Potential Use Cases - Technical analysis: Identifying trends, support/resistance levels, and chart patterns. - Algorithmic trading: Backtesting strategies across multiple timeframes. - Machine learning models: Training predictive models for stock price movements. - Volatility analysis: Understanding market behavior across different timeframes.

The global Amazon S3 Consulting Service market size was valued at USD 459.5 million in 2023 and is projected to reach USD 1,501.9 million by 2033, exhibiting a CAGR of 13.8% during the forecast period. The market growth is attributed to the increasing adoption of cloud computing services and the need for efficient data storage and management solutions. Additionally, the growing demand for data analytics and machine learning applications is further driving the market demand for Amazon S3 Consulting Services. North America is expected to dominate the market throughout the forecast period, owing to the presence of major technology companies and the early adoption of cloud computing services. The market is fragmented with numerous players offering Amazon S3 consulting services. Key market players include Teradata, MicroPyramid, Appnovation Technologies, Cloudticity, Flux7, Intertech, iOLAP, Iosmart, MONEI, OCS Solutions, Progent, Pythian, Quintagroup, Red Wire Services, Shadow-Soft, TekStream Solutions, Zero & One, and others. These companies provide a range of services, including cloud strategy development, data migration, data analytics, and managed services. To gain a competitive edge, market players are focusing on developing innovative solutions and forming strategic partnerships with cloud providers. Market growth is also driven by the emergence of new use cases for Amazon S3, such as big data analytics, machine learning, and content delivery networks. Website:

The Data Lake Market size was valued at USD 5.80 USD Billion in 2023 and is projected to reach USD 28.12 USD Billion by 2032, exhibiting a CAGR of 25.3 % during the forecast period. Recent developments include: April 2023: IBM Corporation announced the launch of a new QRadar Security Suite to accelerate threat detection and response. The launch of the new technology will help improve the productivity of security teams by enabling analysts to respond faster and more efficiently, thereby freeing them up for higher-value work., December 2022: Microsoft and LSEG (London Stock Exchange Group) announced a partnership to use Microsoft Cloud to create the latter’s data infrastructure and develop new data & analytics products and services. This partnership would strengthen its position as the world's leading financial market infrastructure and data provider., November 2022: Dremio, a simple and open data lakehouse, announced key features for updating & writing data, improved support for semi-structured data, and expanded data ecosystem and business intelligence (BI) integrations in the data lakehouse evolution., February 2022: Persistent Systems acquired Data Glove and created a new Microsoft business unit focused on the Azure cloud. The acquisition expanded the delivery capabilities with highly skilled personnel, established a new nearshore distribution center in Costa Rica, and expanded the company's presence in India and the U.S., December 2021: Informatica launched a new solution that democratized access to cloud data lakes on Amazon Web Services (AWS) with AWS Lake Formation. This solution enabled business users at every level within an organization to access their data with improved security and trust to make informed business decisions.. Key drivers for this market are: Rising Demand for Effective Security Solutions Among Organizations to Drive Market Growth. Potential restraints include: Budgetary Issues Among Small-Scale Businesses May Hinder Market Growth. Notable trends are: Growing Implementation of Touch-based and Voice-based Infotainment Systems to Increase Adoption of Intelligent Cars.

The North American cloud computing market, valued at $248.07 million in 2025, is experiencing robust growth, projected to expand significantly over the forecast period (2025-2033). A Compound Annual Growth Rate (CAGR) of 15.23% indicates a substantial increase in market size driven by several factors. The increasing adoption of cloud services by both Small and Medium-sized Enterprises (SMEs) and large enterprises across diverse sectors like manufacturing, healthcare, BFSI (Banking, Financial Services, and Insurance), and government is a primary catalyst. Furthermore, the shift towards digital transformation initiatives, the need for enhanced scalability and flexibility, and the cost-effectiveness of cloud solutions are fueling market expansion. Competitive pressures among major players like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP), and Salesforce are leading to continuous innovation and improved service offerings, further stimulating market growth. The hybrid cloud model, combining public and private cloud infrastructure, is gaining traction due to its ability to address specific security and compliance needs, contributing to the market's dynamism. While data on specific regional breakdowns within North America (United States and Canada) is limited, it's reasonable to assume a significant concentration of market share in the United States, given its advanced technological infrastructure and high adoption rates. The market's growth trajectory is likely to remain strong, driven by ongoing technological advancements and the increasing reliance on cloud-based solutions across various industries. The North American cloud computing market segmentation reveals significant opportunities across various sectors. The public cloud (IaaS, PaaS, SaaS) segment is expected to dominate, reflecting the widespread adoption of cloud-based applications and services. However, the private and hybrid cloud segments are also experiencing growth, driven by security and regulatory compliance requirements. The large enterprise segment contributes a substantial portion of the market revenue, but the SME segment is also showing significant growth potential, indicating a broad-based adoption of cloud technologies. Geographical analysis, while limited by available data, points towards a strong market presence in the United States, given its established technology sector and high adoption rates. However, Canada's growing digital economy suggests increasing cloud adoption within its borders as well. Continued investment in infrastructure, coupled with evolving industry regulations and robust technological innovation, will continue to shape the North American cloud computing market landscape in the coming years. Recent developments include: June 2024: Apple unveiled its cloud intelligence system, Private Cloud Compute (PCC), tailored for cloud-based artificial intelligence (AI) tasks, prioritizing privacy preservation. PCC aims to transfer complex, power-intensive requests to the cloud while guaranteeing that data remains confidential and is never exposed to any third party, including Apple., May 2024: VPS AI unveiled its decentralized cloud computing solutions. The launch of VPS AI marks a significant shift in the cloud computing landscape. VPS AI provides a decentralized solution for establishing virtual private servers and containerized nodes, enabling individuals and enterprises to liberate themselves from the dominance of major tech corporations.. Key drivers for this market are: Robust Shift Towards Digital Transformation Across North America, Advancement of AI and Big Data Analytics. Potential restraints include: Robust Shift Towards Digital Transformation Across North America, Advancement of AI and Big Data Analytics. Notable trends are: Robust Shift Towards Digital Transformation Across North America.

According to estimates, Amazon claimed the top spot among online retailers in the United States in 2023, capturing 37.6 percent of the market. Second place was occupied by the e-commerce site of the retail chain Walmart, with a 6.4 percent market share, followed in third place by Apple, with 3.6 percent.

Amazon’s continued success

Amazon has long dominated the e-commerce market as the world’s favorite online marketplace. In 2022, company hit over half a trillion U.S. dollars in net sales. The United States is by far Amazon’s most profitable market, as the U.S. branch generated over 356 billion U.S. dollars in sales in 2022. Germany ranked second, with 33 billion dollars, followed closely by the United Kingdom with 30 billion dollars.

Online shopping on the rise

Online shopping has grown significantly over the past decade, with more people turning to the internet for their shopping needs. The proof is in the numbers: the U.S. e-commerce industry was worth almost a trillion dollars in 2023. By 2027, forecasts show that the online market will grow to more than 50 percent. U.S. online shoppers purchase fashion and food and beverages the most via the internet.