List of Microsoft Azure Data Lake Storage Customers
Microsoft
One Microsoft Way,
Redmond, 98052-6399, WA,
United States
Redmond, 98052-6399, WA,
United States
1 425-882-8080
Professional Services
228000
$320.0B
Since 2010, our global team of researchers has been studying Microsoft Azure Data Lake Storage customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Microsoft Azure Data Lake Storage for Cloud Storage from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Microsoft Azure Data Lake Storage for Cloud Storage include: Microsoft, a United States based Professional Services organisation with 228000 employees and revenues of $320.00 billion, Wesfarmers, a Australia based Retail organisation with 120000 employees and revenues of $28.86 billion, Tenet Healthcare, a United States based Healthcare organisation with 74480 employees and revenues of $20.67 billion, OpenAI, a United States based Professional Services organisation with 4000 employees and revenues of $13.10 billion, Kao, a Japan based Manufacturing organisation with 32566 employees and revenues of $11.31 billion and many others.
Contact us if you need a completed and verified list of companies using Microsoft Azure Data Lake Storage, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Ferrovie dello Stato Italiane | Transportation | 582 | $180M | Italy | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2022 | n/a |
In 2022, Ferrovie dello Stato Italiane deployed Microsoft Azure Data Lake Storage as the core Cloud Storage backbone for a drone, artificial intelligence and augmented reality enabled construction site monitoring program led by its subsidiaries Italferr and FSTechnology. The initiative began as a 2019 proof of concept on the Napoli to Bari high speed line and evolved into a multi year project encompassing approximately 195 construction sites and some 650 personnel involved in site monitoring and analysis.
The implementation uses Microsoft Azure Data Lake Storage to scale and classify mission data gathered by drone surveys, with Azure Data Factory orchestrating ingestion pipelines and Azure Functions performing post processing of imagery. Azure Synapse aggregates the processed datasets for reporting, while Power BI delivers visualization and dashboards, and Azure Data Explorer is used for photo and telemetry analysis. Azure Cognitive Services and custom machine learning models are applied to detect environmental anomalies such as illegal landfills, leaks and other critical defects, supporting automated quality checks and digital twin generation.
Architecturally the solution connects onsite drone missions to a centralized cloud repository, with Seikey operating survey flights and initial post processing before handing data into the Microsoft cloud stack. The workflow produces 3D digital twin models of construction sites that are consumed by engineers offsite via Microsoft HoloLens for augmented reality visualization and by Microsoft Teams for live collaboration, creating an end to end data flow from field capture to remote inspection.
Governance and process change accompanied the technical rollout, shifting construction management from paper based and manual inspection routines to digital, data driven workflows and centralized storage policies in Cloud Storage. The programme moved from pilot governance to scaled operations, standardizing survey schedules, classification schemas in Azure Data Lake and AI model governance for anomaly detection to support consistent quality assurance across sites.
Outcomes reported by project stakeholders include faster and more efficient monitoring cycles, reduced time and costs for inspections, improved qualitative inspections through AI assisted analysis, and the ability to reallocate specialist engineers to higher value decision making. The team is planning to extend the architecture to post construction maintenance monitoring and to export the methodology to international projects.
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Goodman Group | Construction and Real Estate | 971 | $320M | Australia | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2020 | n/a |
In 2020, Goodman Group implemented Microsoft Azure Data Lake Storage as its primary Cloud Storage repository to centralize enterprise data for construction and real estate operations. Microsoft Azure Data Lake Storage was provisioned to serve as a consolidated storage fabric for asset, project, operational and financial datasets, enabling centralized data management and analytics workflows across the business.
The implementation emphasized category-aligned capabilities of Microsoft Azure Data Lake Storage, including scalable object storage with a hierarchical namespace, support for both structured and unstructured datasets, metadata indexing and lifecycle management. The configuration incorporated role based access controls and encryption at rest, and was organized to support data ingestion pipelines, partitioned landing zones and governed data zones for analytical consumption.
Operational scope covered data engineering and analytics teams supporting asset management, portfolio reporting and operational decisioning, with governance centered on centralized access policies, retention rules and role based permissions. Deployment choices focused on modular storage zones and policy driven data lifecycle, enabling standardized data handling across Goodman Group without reference to a named prior system.
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Kao | Manufacturing | 32566 | $11.3B | Japan | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2023 | n/a |
In 2023, Kao implemented Microsoft Azure Data Lake Storage as a core element of its K25 SAP on Azure program, aligning the company’s data platform strategy with its global SAP renewal and cloud migration initiatives. The deployment was positioned to support Kao’s goal of unified global reporting across Asia, Europe, the US, and Japan and to feed analytics and surround systems used in finance, sales, production, procurement, and inventory management.
Microsoft Azure Data Lake Storage was configured as the primary Cloud Storage layer for consolidated enterprise data, receiving staged extracts from SAP BW and other surround systems. The implementation included structured landing zones and curated layers to support Azure Synapse Analytics consumption, and it used Azure Active Directory for single sign-on and SAML authentication to maintain centralized identity and access control.
The data lake implementation was integrated with Kao’s SAP on Azure architecture and adjacent Azure services, notably Azure Synapse Analytics for analytics workloads and Azure platform services used across the SAP landscape. Connectivity and hybrid operations relied on Azure ExpressRoute for stable on-premise connectivity, and the broader solution coexisted with Azure NetApp Files that provides HANA storage, backups, region-to-region replication between Japan East and Japan West, and mechanisms for rapid system refreshes used in development and verification workflows.
Governance and operational coverage were defined to support global standardization of codes and configurations as part of the K25 program, enabling centralized data access for business units across Kao’s Hygiene and Living Care, Health and Beauty Care, Life Care, Cosmetics, and Chemical businesses. Kao reported early operational benefits tied to Azure services, including reduced monitoring overhead using Azure Monitor, efficient backup and DR patterns, and cost and operational efficiencies from using Azure platforms, while the global rollout and SAP S/4HANA migration program continued with Accenture and Microsoft collaboration.
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Layer 6 | Professional Services | 100 | $30M | Canada | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2019 | n/a |
In 2019, Layer 6 implemented Microsoft Azure Data Lake Storage as its Cloud Storage platform to centralize raw and processed datasets used by its machine learning workflows. The implementation was aligned with the companys Microsoft Azure footprint and aimed to support data science and ML engineering teams based in Toronto, Canada.
The deployment of Microsoft Azure Data Lake Storage was configured to separate landing, curated, and model artifact zones, and to support namespace organization and retention policies common to large scale data lakes. Functional capabilities implemented included persistent data ingestion landing areas, curated feature storage for training, and model artifact storage tied to experiment outputs, reflecting standard Cloud Storage patterns for ML workloads.
Integrations connected Microsoft Azure Data Lake Storage with Azure Data Factory for orchestrated data ingestion, with Azure Databricks for feature engineering and batch processing, and with Azure Kubernetes Service for downstream model serving and operational workflows. Operational coverage focused on the machine learning lifecycle, including data preparation, feature engineering, model training, and artifact consumption by production inference services.
Governance and process changes emphasized MLOps practices led by the companys Machine Learning Engineers, incorporating role based access controls and storage account level policies to manage data access and lifecycle. The implementation established a unified Cloud Storage backbone for analytics and MLOps, with architecture and workflows designed to enable reproducible experiments and controlled data access for analytics and production ML use cases.
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Microsoft | Professional Services | 228000 | $320.0B | United States | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2019 | n/a |
In 2019, Microsoft deployed Microsoft Azure Data Lake Storage as a Cloud Storage backbone to support an AI driven finance chatbot initiative for its Procure to Pay process. The deployment was coordinated by Microsoft Finance Engineering within Core Services Engineering and Operations and formed a central storage and analytics layer for a project that consolidated sixteen discrete services into a unified end to end user experience.
The implementation combined conversational AI components including Azure Bot Service, Microsoft LUIS, QnA Maker, and Microsoft Azure Cognitive Services with data processing services such as Azure Databricks and Microsoft Azure Stream Analytics. Microsoft Azure Data Lake Storage was used to house big data and streaming inputs, providing persistent storage for text analytics outputs and telemetry captured by Application Insights and Kusto for Live Site monitoring.
Architecturally the solution layered a user interaction tier supporting multiple channels including Cortana, an AI orchestration tier for intent detection and contextual handoff, a microservices integration tier built on Azure Service Fabric, and a Cloud Storage and analytics tier anchored by Microsoft Azure Data Lake Storage. Event ingestion and messaging were handled through Microsoft Azure Event Hubs and stream processing pipelines fed into Databricks and Stream Analytics for downstream consumption by the digital assistant and reporting systems.
Governance and process changes emphasized a services oriented architecture and an end to end user experience design, moving teams away from system centric siloed applications toward reusable microservices and conversational workflows. The chatbot design prioritized intent resolution across multiple contexts and automation of routine Procure to Pay tasks, with operational monitoring instrumented through Application Insights and Kusto to support live site operations.
The stated goals for the Microsoft Azure Data Lake Storage centered on enabling scalable integration of analytics and conversational capabilities, simplifying the employee experience by reducing clicks and context switching, and abstracting application complexity through microservices. The architecture was explicitly designed for scalability and integration with other vertical services within Microsoft finance.
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Construction and Real Estate | 7289 | $1.3B | Australia | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2019 | n/a |
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Professional Services | 4000 | $13.1B | United States | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2022 | n/a |
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Professional Services | 2000 | $300M | United States | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2021 | n/a |
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Manufacturing | 29207 | $4.1B | Austria | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2020 | oh22 |
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Banking and Financial Services | 7300 | $1.7B | Germany | Microsoft | Microsoft Azure Data Lake Storage | Cloud Storage | 2021 | n/a |
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Buyer Intent: Companies Evaluating Microsoft Azure Data Lake Storage
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- Tata Group, a India based Professional Services organization with 1028000 Employees
Discover Software Buyers actively Evaluating Enterprise Applications
| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD Microsoft Azure Data Lake Storage Coverage
Microsoft Azure Data Lake Storage is a Cloud Storage solution from Microsoft.
Companies worldwide use Microsoft Azure Data Lake Storage, from small firms to large enterprises across 21+ industries.
Organizations such as Microsoft, Wesfarmers, Tenet Healthcare, OpenAI and Kao are recorded users of
Microsoft Azure Data Lake Storage for Cloud Storage.
Companies using Microsoft Azure Data Lake Storage are most concentrated in Professional Services, Retail and Healthcare, with adoption spanning over 21 industries.
Companies using Microsoft Azure Data Lake Storage are most concentrated in United States, Australia and Japan, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Microsoft Azure Data Lake Storage across Americas, EMEA, and APAC.
Companies using Microsoft Azure Data Lake Storage range from small businesses with 0-100 employees - 6.67%, to mid-sized firms with 101-1,000 employees - 13.33%, large organizations with 1,001-10,000 employees - 33.33%, and global enterprises with 10,000+ employees - 46.67%.
Customers of Microsoft Azure Data Lake Storage include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified Microsoft Azure Data Lake Storage customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Cloud Storage.