List of One Model Data Mesh ETL Customers
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United States
Since 2010, our global team of researchers has been studying One Model Data Mesh ETL 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 One Model Data Mesh ETL for Extract, Transform, and Load (ETL) 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 One Model Data Mesh ETL for Extract, Transform, and Load (ETL) include: Pure Storage, a United States based Professional Services organisation with 6000 employees and revenues of $3.17 billion, Tabcorp, a Australia based Leisure and Hospitality organisation with 5000 employees and revenues of $1.72 billion, Squarespace, a United States based Professional Services organisation with 1749 employees and revenues of $1.01 billion and many others.
Contact us if you need a completed and verified list of companies using One Model Data Mesh ETL, 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.
The One Model Data Mesh ETL 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 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 | Insight Source |
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Pure Storage | Professional Services | 6000 | $3.2B | United States | One Model | One Model Data Mesh ETL | Extract, Transform, and Load (ETL) | 2018 | n/a | In 2018, Pure Storage deployed One Model Data Mesh ETL to centralize HR and recruiting datasets from Workday, Greenhouse and Glint, accelerating people analytics and enabling identification of high performing sales hiring channels. The One Model Data Mesh ETL implementation used an Extract, Transform, and Load (ETL) approach to connect multiple source systems into a unified analytics layer and delivered dashboards within a week of data access. The scope targeted HR and recruiting datasets to provide consolidated talent analytics and channel performance analysis for hiring managers and HR operations. Implementation centered on automated ingestion pipelines, transformation and schema harmonization, and a unified people analytics data model that fed dashboard provisioning and reporting workflows. Integrations explicitly included Workday, Greenhouse and Glint, with orchestration to normalize hires, candidate sources and engagement feedback into consistent HR metrics. Governance emphasized a centralized dataset for HR and recruiting teams to shorten analytic cycles and enable faster, scalable HR insights. | |
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Squarespace | Professional Services | 1749 | $1.0B | United States | One Model | One Model Data Mesh ETL | Extract, Transform, and Load (ETL) | 2017 | n/a | In 2017, Squarespace implemented One Model Data Mesh ETL to connect recruiting, HRIS and facilities data during a period of high growth. The One Model Data Mesh ETL, categorized as Extract, Transform, and Load (ETL), ingested Greenhouse recruiting feeds, UltiPro HRIS records, and facilities datasets to produce unified HR dashboards and enable real-time reporting for HR stakeholders in the United States. The implementation established a centralized data mesh layer and ETL pipelines that normalized disparate schemas into a canonical employee model, supporting standardization of headcount, hiring and retention views. Operational coverage focused on recruiting, HR operations and facilities teams, with configuration of role-based dashboards and access controls to align reporting with hiring and retention decision-making. Governance emphasized a common data model and reporting cadence to ensure consistency across HR stakeholders, and the unified One Model Data Mesh ETL outputs were used to improve hiring and retention decision-making as stated in the case study. | |
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Tabcorp | Leisure and Hospitality | 5000 | $1.7B | Australia | One Model | One Model Data Mesh ETL | Extract, Transform, and Load (ETL) | 2020 | n/a | In 2020 Tabcorp implemented One Model Data Mesh ETL to consolidate 14 disjointed HR systems and establish a single source of truth for HR metrics. The implementation is categorized as Extract, Transform, and Load (ETL) and focused on unifying HR metrics and reporting across the enterprise. The One Model Data Mesh ETL deployment ingested and harmonized seven years of historical HR data and established daily refreshed datasets from many source systems, supporting centralized metric definitions and standardized HR dimensions. Configuration included extract and transform pipelines, a governed metrics layer for people analytics, and automated refresh orchestration to maintain up to date headcount, attrition, and payroll-related indicators. Integrations spanned the set of existing HR and payroll systems, using daily data feeds to populate the centralized model, and the solution served HR and finance users across Tabcorp’s Australian states. The workstream emphasized data consolidation and cross functional data access to align operational HR reporting with finance reconciliation processes. Governance changes formalized the single source of truth, enabling metric stewardship and consistent reporting workflows for managers and analytics teams. The project delivered explicit outcomes, saving an estimated 30,000 manager hours and approximately $2.5M in the first year, and improving HR and finance alignment across Australian states. |
Buyer Intent: Companies Evaluating One Model Data Mesh ETL
- Bank of Montreal, a Canada based Banking and Financial Services organization with 53597 Employees
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