List of Microsoft SQL Server 2017 Machine Learning Services 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 SQL Server 2017 Machine Learning Services 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 SQL Server 2017 Machine Learning Services for ML and Data Science Platforms 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 SQL Server 2017 Machine Learning Services for ML and Data Science Platforms include: Dell, a United States based Manufacturing organisation with 108000 employees and revenues of $95.60 billion, HDFC Bank, a India based Banking and Financial Services organisation with 214521 employees and revenues of $23.22 billion, PNB MetLife, a India based Insurance organisation with 10000 employees and revenues of $3.20 billion, Acxiom, a United States based Professional Services organisation with 3650 employees and revenues of $650.0 million, Worldsmart, a Australia based Professional Services organisation with 100 employees and revenues of $10.0 million and many others.
Contact us if you need a completed and verified list of companies using Microsoft SQL Server 2017 Machine Learning Services, 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 Machine Learning software purchases.
The Microsoft SQL Server 2017 Machine Learning Services customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of Machine Learning software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Acxiom | Professional Services | 3650 | $650M | United States | Microsoft | Microsoft SQL Server 2017 Machine Learning Services | ML and Data Science Platforms | 2015 | n/a |
In 2015, Acxiom implemented Microsoft SQL Server 2017 Machine Learning Services as part of its ML and Data Science Platforms footprint. The deployment was intended to centralize advanced analytics capabilities for marketers, brand managers, data scientists, mathematicians, statisticians, and programmers across the organization.
The implementation emphasizes in-database machine learning capabilities, including model training, clustering algorithms, and scoring workflows for both structured and unstructured big data queries. Functional configuration reflects support for R-based analytical workflows, consistent with the organization’s use of SQL Server 2016 with R Services to create complex models and advanced analytics pipelines.
Operational scope covers analytics and marketing functions that deliver multidimensional insights to Acxiom customers, with the platform serving as the primary runtime for model development, batch scoring, and iterative analytics. Governance and process changes focused on consolidating model development and deployment into the database platform, aligning analytics workflows and tooling with the Microsoft SQL Server 2017 Machine Learning Services environment to support enterprise-level data science collaboration.
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Dell | Manufacturing | 108000 | $95.6B | United States | Microsoft | Microsoft SQL Server 2017 Machine Learning Services | ML and Data Science Platforms | 2017 | n/a |
In 2017 Dell upgraded its internal database platform to Microsoft SQL Server 2017 Machine Learning Services as part of its ML and Data Science Platforms to support analytics and data science workloads across manufacturing, marketing, finance and e-commerce. Dell operates roughly 25,000 SQL Server databases that power more than 1,500 applications, and the upgrade was applied to internal database management tooling to expose new in-database analytics capabilities to application teams.
The implementation centered on two internally developed systems, SQL Dashboard and SQL Grid, which were configured to leverage Microsoft SQL Server 2017 Machine Learning Services. SQL Dashboard provides database asset management, performance monitoring and health assessment, including storage and compute sufficiency checks. SQL Grid functions as a private cloud pooling virtual machines for rapid provisioning of SQL Server databases, enabling short lived test and development instances that teams can request and release back to the pool.
Operational coverage spans approximately 1,000 Dell architects, system engineers, application developers and database administrators worldwide, with SQL Dashboard used for ongoing monitoring and SQL Grid used for self-service provisioning. The deployment enabled teams to instantiate databases with Machine Learning Services enabled, giving immediate access to in-database R and Python runtimes for analytics and model development.
As an explicit outcome Dell reported that a team was able to spin up a database with Machine Learning Services in SQL Grid in one hour instead of waiting two to three months, and they were able to use R and Python within an hour of their request. The upgrade therefore provided very fast access to new SQL Server 2017 features across Dell’s business functions.
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HDFC Bank | Banking and Financial Services | 214521 | $23.2B | India | Microsoft | Microsoft SQL Server 2017 Machine Learning Services | ML and Data Science Platforms | 2017 | n/a |
In 2017, HDFC Bank implemented Microsoft SQL Server 2017 Machine Learning Services to build scorecards for loan applications. HDFC Bank, the largest private bank in India by market capitalization, focused the Microsoft SQL Server 2017 Machine Learning Services deployment on credit risk modeling to support faster underwriting and more consistent decisioning across retail and corporate lending functions.
The deployment leveraged in-database machine learning and model scoring capabilities typical of ML and Data Science Platforms, enabling analysts and data scientists to prepare data, train models, and operationalize scorecards without exporting large datasets. By using Microsoft SQL Server 2017 Machine Learning Services the bank centralized model development workflows, supported iterative model training and scoring pipelines, and reduced pre-processing overhead so teams could spend more time building predictive models.
Operational coverage included bank analysts, data scientists, and loan officers within lending and underwriting teams, who consumed scorecard outputs within existing loan decision workflows. The implementation emphasized embedded scoring and automated scoring pipelines to deliver model outputs directly to loan officers for faster decisions, while retaining core data governance and model artifacts inside the database environment.
Governance focused on standardizing scorecard development, validation, and rollout processes across lending teams, aligning operational scoring with model governance practices. HDFC Bank reported that analysts and data scientists spent less time preparing data and more time building accurate predictive models, loan officers could make better, faster decisions, and the bank advanced its credit risk modeling capability using Microsoft SQL Server 2017 Machine Learning Services.
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PNB MetLife | Insurance | 10000 | $3.2B | India | Microsoft | Microsoft SQL Server 2017 Machine Learning Services | ML and Data Science Platforms | 2020 | n/a |
In 2020 PNB MetLife implemented Microsoft SQL Server 2017 Machine Learning Services as its ML and Data Science Platforms component to support operational analytics and persistency modeling. The Microsoft SQL Server 2017 Machine Learning Services deployment was positioned to enable in-database model scoring and algorithmic workflows that fed daily operational reporting and financial analytics.
The implementation configuration combined Microsoft SQL Server 2017 Machine Learning Services with existing MS SQL based pipelines and Oracle SQL Developer scripts for daily reporting. Cognos was used for automated financial reporting, while models and scoring outputs from Microsoft SQL Server 2017 Machine Learning Services were incorporated into retention and surrender prediction workflows, and into support processes for retention payouts, eNach, and Direct Debit.
Operational scope covered cross-functional collaboration between Business Intelligence Unit, IT, operations, financial planning, and customer communications. Governance and process changes were centered on joint analytics review cycles, shared data pipelines for daily reporting, and coordinated model validation with BIU and IT to drive sharper surrender prediction and persistency analysis.
The environment was used to analyze levers for 13th, 37th and 49th month persistency and to automate reporting for forecasting and strategy planning over a five year horizon. Microsoft SQL Server 2017 Machine Learning Services served as the analytics execution and operational scoring layer within the broader ML and Data Science Platforms footprint at PNB MetLife.
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Worldsmart | Professional Services | 100 | $10M | Australia | Microsoft | Microsoft SQL Server 2017 Machine Learning Services | ML and Data Science Platforms | 2015 | n/a |
In 2015, Worldsmart implemented Microsoft SQL Server 2017 Machine Learning Services as part of its ML and Data Science Platforms stack. The deployment was positioned to host in-database analytic workflows and operational model scoring for the firm’s forecasting use cases.
Microsoft SQL Server 2017 Machine Learning Services was configured to execute R-based analytics inside the database, enabling persistent model artifacts and scheduled scoring jobs. The configuration emphasized in-database execution and model operationalization, delivering repeatable inferencing through stored procedures and automated batch scoring pipelines.
The SQL Server Machine Learning deployment was integrated with Azure Stream Analytics services for streaming input and with R Server for model training and experimentation, while Power BI was chosen as the presentation layer to reduce the technical burden of visualization and report delivery. The implementation tied data ingestion, model scoring, and interactive reporting together to support Worldsmart’s machine learning forecasts and analysis workflows within its analytics and decision support processes.
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Buyer Intent: Companies Evaluating Microsoft SQL Server 2017 Machine Learning Services
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FAQ - APPS RUN THE WORLD Microsoft SQL Server 2017 Machine Learning Services Coverage
Microsoft SQL Server 2017 Machine Learning Services is a ML and Data Science Platforms solution from Microsoft.
Companies worldwide use Microsoft SQL Server 2017 Machine Learning Services, from small firms to large enterprises across 21+ industries.
Organizations such as Dell, HDFC Bank, PNB MetLife, Acxiom and Worldsmart are recorded users of
Microsoft SQL Server 2017 Machine Learning Services for ML and Data Science Platforms.
Companies using Microsoft SQL Server 2017 Machine Learning Services are most concentrated in Manufacturing, Banking and Financial Services and Insurance, with adoption spanning over 21 industries.
Companies using Microsoft SQL Server 2017 Machine Learning Services are most concentrated in United States, India and Australia, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Microsoft SQL Server 2017 Machine Learning Services across Americas, EMEA, and APAC.
Companies using Microsoft SQL Server 2017 Machine Learning Services range from small businesses with 0-100 employees - 20%, to mid-sized firms with 101-1,000 employees - 0%, large organizations with 1,001-10,000 employees - 40%, and global enterprises with 10,000+ employees - 40%.
Customers of Microsoft SQL Server 2017 Machine Learning Services 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 SQL Server 2017 Machine Learning Services customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of ML and Data Science Platforms.