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.
Apply Filters For 10+ Million Software Purchases
- Analytics and BI
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
 |
Microsoft | Professional Services | 221000 | $243.0B | United States | Microsoft | Microsoft Power BI | Analytics and BI | 2016 | n/a | ||
|
|
Microsoft | Professional Services | 221000 | $243.0B | United States | Microsoft | Microsoft Azure Stream Analytics | Analytics and BI | 2019 | n/a | In 2019 Microsoft deployed Microsoft Azure Stream Analytics as a core streaming layer for an AI driven finance chatbot initiative aimed at rearchitecting the Procure to Pay process. This implementation placed Microsoft Azure Stream Analytics inside an Analytics and BI footprint to centralize streaming telemetry and big data processing across finance services and to support conversational automation within procurement and payment workflows. The implementation consolidated 16 discrete Procure to Pay services into a single end to end user experience layer, and instrumented conversational and analytics capabilities using Azure Bot Service, Microsoft LUIS also known as Language Understanding, QnA Maker, Microsoft Azure Cognitive Services, and Azure Text Analytics. Microsoft Azure Stream Analytics handled live stream processing, feeding downstream analytics in Azure Databricks and Azure Data Lake Storage while Application Insights and Kusto provided Live Site monitoring and diagnostics. Micro services built on Azure Service Fabric abstracted system complexity and exposed APIs and master data to the unified UX. Integrations were explicitly implemented with Azure Event Hubs for ingesting event streams, with multiple user channels including Cortana for interaction, and with the broader Microsoft cognitive and bot services stack to enable intent detection and context switching. Operational ownership rested with Core Services Engineering and Operations and the Microsoft Finance Engineering team, focused on finance workflows for procurement and payment across the organization. Governance and process changes emphasized a shift from a system centric collection of siloed apps to a user centric, AI first services oriented architecture, with bots designed to determine user intent, move fluidly across contexts, and perform process actions to reduce manual handoffs. The architecture was designed with scalability in mind and integration points to many vertical services, and the stated objective was to simplify employee experience and provide important information with fewer clicks. | |
 |
|
Professional Services | 221000 | $243.0B | United States | Microsoft | Microsoft Azure Databricks (AI) | Analytics and BI,Data Warehouse | 2019 | n/a |
|
|
|
|
|
Professional Services | 221000 | $243.0B | United States | SAP | SAP BW/4HANA | Data Warehouse | 2018 | n/a |
|
|
|
|
|
Professional Services | 221000 | $243.0B | United States | LexisNexis | Lex Machina | Analytics and BI | 2016 | n/a |
|
|
|
|
|
Professional Services | 90 | $14M | Netherlands | Microsoft | Microsoft Power BI | Analytics and BI | 2022 | n/a |
|
|
|
|
|
Professional Services | 10 | $1M | United States | Umami | Umami | Analytics and BI | 2022 | n/a |
|
|
|
|
|
Manufacturing | 53000 | $37.4B | United States | Microsoft | Microsoft Power BI | Analytics and BI | 2016 | n/a |
|
|
|
|
|
Manufacturing | 53000 | $37.4B | United States | Cloudera | Cloudera Hortonworks Data Platform | Data Warehouse | 2017 | n/a |
|
|
|
|
|
Manufacturing | 53000 | $37.4B | United States | Cloudera | Cloudera Enterprise Platform | Data Warehouse | 2013 | n/a |
|
|