Introduction

Microsoft Azure Statistics: Microsoft Azure is a leading cloud computing platform, contributing significantly to Microsoft's Intelligent Cloud segment, which reported $24.1 billion in revenue during Q3 2024, reflecting a 20% year-over-year increase. Azure holds a 20% share of the global cloud infrastructure market, positioning it as the second-largest provider after Amazon Web Services (AWS), which commands a 31% share. The platform serves approximately 486,738 organizations worldwide, with 85% of Fortune 500 companies utilizing its services.

Microsoft has invested over $108 billion in expanding its cloud infrastructure, including the development of more than 60 AI data centers globally. This strategic investment has facilitated the integration of advanced technologies such as machine learning and AI into Azure's offerings.

This article will discuss in detail the Microsoft Azure statistics, focusing on important indicators and metrics such as market shares, revenue figures, and strategic initiatives.

Microsoft Azure's global cloud infrastructure continues to expand, with 93 availability zones (AZs) spanning 33 regions as of 2024. Europe leads the way with 33 AZs, followed closely by the Americas with 27. This distribution highlights Azure's commitment to providing robust and reliable cloud services across diverse geographic locations, ensuring low-latency access and data redundancy for its customers worldwide. Comparing cloud giants While Azure boasts a significant presence, it faces stiff competition from other major cloud providers. Google Cloud Platform operates data centers in 40 regions with a total of 121 AZs, surpassing Azure's count. Europe remains a key focus for both providers, with Google Cloud hosting 36 AZs in the region. Amazon Web Services (AWS) also maintains a strong global footprint with 34 geographic regions and a particularly dense presence in Europe, the Middle East, Africa, Asia Pacific, and China, which collectively account for over 70 percent of AWS's total AZs. Regional distribution and market dynamics The concentration of AZs in Europe across multiple providers underscores the region's importance in the global cloud market. While operating on a smaller scale, IBM data centers host 43 AZs worldwide, prioritizes the Americas with 19 zones. Similarly, Oracle Cloud Infrastructure data centers, with 50 AZs globally, places emphasis on Europe with 15 AZs. This regional focus among various providers indicates a competitive landscape where strategic placement of infrastructure plays a crucial role in meeting customer demands and regulatory requirements.

As of March 2025, a total of over 58,000 products and services were offered on the Microsoft Azure marketplace, of which 10,165 belong to the IT and management tools category. The Azure marketplace is a digital catalogue on which independent software vendors can list their products and services. This enables Azure customers to pick from a variety of solutions that runs on Azure to cater to their specific needs.

In the third quarter of financial year 2025, Microsoft Azure revenue growth stood at 33 percent. Azure is Microsoft's cloud computing service that is used for creating a variety of scalable solutions for different use-cases. Azure's biggest competitors are Amazon Web Services (AWS) and Google Cloud. Microsoft Azure revenue Microsoft does not publish exact details of revenue derived from Azure. Instead, revenues from Azure are integrated in its intelligent cloud segment, which consists of public, private, and hybrid server products and cloud services. In 2021, the intelligent cloud segment generated revenues of over 60 billion U.S. dollars, with Azure driving up server products and cloud services revenues specifically. However, Microsoft’s intelligent cloud also features other high-value products, including consulting services and premier support services. Microsoft Azure products and services Through its Azure platform, Microsoft offers a variety of different cloud computing resources to its customers, including virtual desktop, SQL database, or serverless Kubernetes. In mid-2021, there were a total of almost 16,000 products and services offered on the Microsoft Azure marketplace, with the majority listed under the IT and management tools category. The market has responded well to Azure's pricing strategy, with nearly a third of all respondents to a global survey of IT professionals rating Azure as providing the best value for money, more than any other provider

The Data Monetization Market size was valued at USD 4.05 billion in 2023 and is projected to reach USD 20.19 billion by 2032, exhibiting a CAGR of 25.8 % during the forecasts period. The data monetization market refers to the actual steps of taking large amounts of unstructured data and transforming them into income-earning products or new business models. Businesses collect data, process and monetize them as information that they are able to sell them to other businesses or use it for the organization’s benefit such as running operations efficiently, making better decisions and making clients’ experiences better. Some of the uses include; selling the compiled consumer data to marketers, providing data services such as predeterminant analysis and letting out copyright consumer data to research firms. The concepts of its use are versatile and can be applied to retail sales, finance, health care, telecommunications, and others. Some important trends of data management are the use of big data and artificial intelligence and machine learning for analysis, burgeoning use of data markets, and legal changes related to data protection and data ownership. Since data is gaining more currency in the management of organizations, the organizations are now employing intelligent technologies and techniques to monetize on the data resources that are available to bring competitive advantage. Recent developments include: In February 2024, Gulp Data announced a partnership with Snowflake that enables organizations to explore, share, and unlock value from their data, providing data valuation, data-backed loans, and data monetization services. , In December 2023, Thales completed the acquisition of Imperva. By providing the most comprehensive solutions for the broadest range of application, data security, and identity use cases, Thales and Imperva will help customers address cybersecurity challenges that are increasing rapidly in frequency, severity, and complexity. , In September 2022, SAS declared SAS Viya on Azure as a powerful data analytics platform available on the Microsoft Azure marketplace. This new offering makes it easier than ever for businesses to gain insights from their data by combining the scalability and flexibility of Azure with the power of SAS Viya. , In March 2022, Domo, Inc. announced Data Apps, a new low-code data tool designed to make data-driven decisions and actions accessible to everyone in an organization. It makes Data Apps more accessible to a wider range of users than traditional BI tools, often specifically designed for executives, managers, and data analysts. , In January 2022, Revelate Data Monetization Corp. formerly known as TickSmith announced a $20 million Series, a funding investment to promote its innovative data-selling platform. Unlike any other product now available, its data web store is a B2B SaaS platform offering an e-commerce data shopping experience by offering all the tools required to prepare, manage, package, and monetize data. .

Explore comprehensive insights in Leads Rank TLD profiles, featuring detailed information for .azure. Utilize our API for efficient data access.

This dataset is about book subjects. It has 3 rows and is filtered where the books is Azure data engineering cookbook : get well versed with different data engineering techniques with Azure data services usinf this recipe-based guide. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

This dataset provides information about the number of properties, residents, and average property values for Azure Lane cross streets in Vista, CA.

The Enterprise Data Lake Solution market is experiencing robust growth, driven by the increasing need for organizations to store and analyze vast amounts of structured and unstructured data from diverse sources. The market's expansion is fueled by the rising adoption of cloud-based solutions, the proliferation of big data analytics, and the imperative for businesses to gain actionable insights from their data for improved decision-making and competitive advantage. Key players like SAP, Microsoft, and Snowflake are significantly contributing to market growth through continuous innovation and expansion of their data lake offerings. The market's segmentation reflects the diverse needs of various industries, with solutions tailored for specific applications across finance, healthcare, and retail. While data security and integration complexities remain significant challenges, ongoing technological advancements in data governance and management are mitigating these concerns. We project a Compound Annual Growth Rate (CAGR) of approximately 15% from 2025 to 2033, leading to substantial market expansion during this period. The competitive landscape is characterized by a mix of established technology giants and specialized vendors. The presence of both large enterprises and niche players indicates a high level of innovation and competition within the market. While some companies focus on comprehensive platform offerings, others specialize in specific data lake components or services. This fragmentation creates both opportunities and challenges for market participants. Future growth hinges on the continued development of advanced analytics capabilities, improved data accessibility, and enhanced security measures within data lake platforms. Strategic partnerships and acquisitions will likely play a key role in shaping the future competitive dynamics of the market. Geographical expansion, particularly in developing economies, also presents significant potential for market expansion.

Manual analysis performed onsite versus Automated analysis performed by Azure cloud server.

The Microsoft Azure Consulting Service market has emerged as a vital component of modern business operations, enabling organizations to harness the power of cloud computing for enhanced efficiency and scalability. As more companies transition to cloud-based solutions, Azure's consulting services have become instrume

This dataset provides information about the number of properties, residents, and average property values for Azure Street cross streets in Oneonta, AL.

Monthly production of extracted minerals.

Introduction

Microsoft Statistics: Microsoft is one of the world’s biggest technology companies, known for products like Windows, Office, and Azure. It has millions of users worldwide and plays a major role in software, cloud computing, and artificial intelligence. The company constantly grows, with high revenue and a strong customer base. Microsoft’s market value is in the trillions, making it one of the most valuable companies.

It also invests in innovation, security, and sustainability. With services like Xbox and LinkedIn, Microsoft reaches different industries. The company’s statistics show steady growth, strong profits, and a major impact on global technology. Its success comes from continuous improvements and adapting to new trends in the digital world.

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The cloud data warehouse solutions market is experiencing robust growth, driven by the increasing need for scalable, cost-effective, and readily accessible data storage and analytics solutions across diverse industries. The market's expansion is fueled by several key factors: the rising adoption of cloud computing, the exponential growth of data volume, the demand for real-time analytics and business intelligence (BI), and the increasing sophistication of data warehousing technologies. Organizations across finance, government, and enterprise sectors are migrating their on-premise data warehouses to the cloud to leverage its inherent benefits like enhanced scalability, pay-as-you-go pricing models, and improved collaboration capabilities. This shift is further propelled by the need for faster data processing speeds and the integration of advanced analytics techniques such as machine learning and AI to extract actionable insights from vast datasets. Competition among major players like Amazon, Google, Microsoft, and Snowflake is intensifying, leading to continuous innovation and feature enhancements within their cloud data warehouse offerings. This competitive landscape benefits end-users, fostering price competitiveness and promoting the development of cutting-edge data warehousing technologies. The market segmentation reveals a dynamic interplay between various application areas and solution types. While the enterprise sector currently dominates market share, significant growth is expected in the government and finance sectors as they increasingly embrace cloud-based solutions for compliance, security, and enhanced operational efficiency. Similarly, Data Warehouse Platforms are currently more prevalent, yet the demand for Data Warehouse Tools and Services segments is rapidly accelerating, indicating a shift towards more specialized and customized solutions catered to specific business requirements. Geographic distribution shows North America and Europe as currently leading regions, yet the Asia-Pacific region, particularly China and India, exhibits significant growth potential owing to rapid technological advancements and increased digital transformation initiatives. This presents substantial opportunities for existing and emerging players, with the market expected to witness considerable expansion over the next decade.

A dataset of body tracking information is presented. The dataset consists of 315 captured walking sequences. Each sequence is simultaneously captured by two Azure Kinect devices. The two captures are interleaved to effectively double the frame rate. Fifteen participants partook in this experiment. Each experiment consists of seven walking actions, and having three predefined trajectories per experiment. That results in 21 sequences per participant. The data were collected using the Azure Kinect Sensor SDK. They were later processed using the official tools and libraries provided by Microsoft. For each sequence and trajectory, the positions and orientations of thirty-two tracked joints were obtained and saved.

The dataset is structured as follows. The experiments from each subject are saved in a single directory. Each directory contains multiple JSON files of timestamped body tracking information to enable the fusion of the two device streams. A calibration file is also provided, enabling the mapping of the coordinates between the two Azure Kinect devices capturing the data (mapping the coordinates of the device known as the Subordinate device to the Master device coordinate system). This data can be used to train neural networks for human motion prediction tasks or test pre-existing algorithms on Azure Kinect data. This dataset could also aid in gait recognition and analysis, as well as in performing action recognition and other surveillance activities.

Journal Publication Citation: Charli Posner, Adrián Sánchez-Mompó, Ioannis Mavromatis, Mustafa Al-Ani, A dataset of human body tracking of walking actions captured using two Azure Kinect sensors, Data in Brief, Volume 49, 2023, 109334, ISSN 2352-3409, https://doi.org/10.1016/j.dib.2023.109334. (https://www.sciencedirect.com/science/article/pii/S2352340923004523)

In a new effort to make our research transparent and reproducible by others, we developed a workflow to run computational studies on a public cloud. It uses Docker containers to create an image of the application software stack. We also adopt several tools that facilitate creating and managing virtual machines on compute nodes and submitting jobs to these nodes. The configuration files for these tools are part of an expanded "reproducibility package" that includes workflow definitions for cloud computing, in addition to input files and instructions. This facilitates re-creating the cloud environment to re-run the computations under the same conditions. The present Zenodo dataset contains all secondary data required to reproduce the figures of the manuscript ("Reproducible Workflow on a Public Cloud for Computational Fluid Dynamics") without running the CFD simulations again. Corresponds to GitHub repository https://github.com/barbagroup/cloud-repro, plus secondary data files (not version-controlled). Funded by NSF Grant No. CCF-1747669.

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