Apps Purchases: 10+ Million Software Purchases
Founded in 2010, APPS RUN THE WORLD is a leading technology intelligence and market-research company devoted to the application space. Leveraging a rigorous data-centric research methodology, we ask the simple B2B sales intelligence question: Who’s buying enterprise applications from whom and why?
Our global team of 50 researchers has been studying the digital transformation initiatives being undertaken by 2 million + companies including technographic segmentation of 10 million ERP, EPM, CRM, HCM, Procurement, SCM, Treasury software purchases, 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.
Apps Run The World Buyer Insight and Technographics Customer Database has over 100 data fields that detail company usage of emerging technologies such as AI, Machine Learning, IoT, Blockchain, Autonomous Database, and different on-prem and cloud apps by function, customer size (employees, revenues), industry, country, implementation status, year deal won, partner involvement, Line of Business Key Stakeholders and key decision-makers contact details, including the systems being used by Fortune 1000 and Global 2000 companies.
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- Analytics and BI
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Molnlycke Health Care UK | Life Sciences | 700 | $143M | United Kingdom | IBM | IBM Cognos Analytics | Analytics and BI | 2009 | n/a | ||
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Kushki | Banking and Financial Services | 628 | $143M | Ecuador | Grafana Labs | Grafana Cloud | Analytics and BI | 2023 | n/a | In 2023 Kushki consolidated metrics, logs, and traces into Grafana Cloud to centralize observability for its digital payments platform in Latin America, implementing Grafana Cloud within the Analytics and BI category. The program targeted platform reliability and troubleshooting workflows across payments operations and engineering teams. Kushki purchased Grafana Cloud via AWS Marketplace and deployed hosted Grafana together with Prometheus for metrics ingestion, dashboards, alerting, and trace correlation. Grafana Cloud served as the central analytics and visualization layer while Prometheus handled time series metrics collection, and log and trace data were consolidated into the same observability workspace. The implementation centralized observability across the digital payments platform, enabling engineering and operations teams to correlate business level signals with technical telemetry. Integrations prioritized instrumenting payment API response metrics, application traces, and centralized logs to support incident triage and root cause analysis. Operational outcomes reported by Kushki included reduced troubleshooting time and improved correlation of business and technical signals, and Grafana Cloud usage contributed to a reduction in API response times with a noted 3 second improvement in one API path. The deployment via AWS Marketplace delivered a hosted, managed observability stack to support ongoing operations and monitoring. | |
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Professional Services | 996 | $143M | United States | Microsoft | Microsoft Power BI | Analytics and BI | 2022 | n/a |
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Government | 1650 | $144M | United Kingdom | Oracle | Oracle OBIEE | Analytics and BI | 2012 | n/a |
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Consumer Packaged Goods | 681 | $144M | United Kingdom | SAP | SAP BW (Business Warehouse) | Data Warehouse | 2015 | n/a |
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Consumer Packaged Goods | 681 | $144M | United Kingdom | Microsoft | Microsoft Power BI | Analytics and BI | 2015 | n/a |
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Banking and Financial Services | 600 | $144M | United States | Tableau Software | Tableau | Analytics and BI | 2020 | n/a |
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Manufacturing | 367 | $144M | United Kingdom | IBM | IBM Cognos Analytics | Analytics and BI | 2019 | Aramar Solutions |
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Professional Services | 500 | $144M | United States | Palantir Technologies | Palantir Foundry | Analytics and BI | 2024 | n/a |
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Education | 1500 | $145M | United States | Domo | Domo | Analytics and BI | 2017 | n/a |
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