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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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | VAR/SI | Insight | Insight Source |
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Eli Lilly | Life Sciences | 50605 | $65.2B | United States | Snowflake | Snowflake Data Warehouse | Data Warehouse | 2019 | n/a | ||
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Astellas Pharma US | Life Sciences | 3000 | $700M | United States | Amazon Web Services (AWS) | Amazon Redshift | Data Warehouse | 2021 | n/a | In 2021, Astellas Pharma US migrated core analytics and master data workloads to Amazon Redshift as its Data Warehouse platform. The engagement pursued two primary objectives, replacing multiple external vendor supplied datasets feeding the Customer Master in the MDM Hub and migrating ETL processes from IBM Netezza Appliance and IBM Data Stage to an AWS Redshift based architecture with subsequent conversion to Talend. The implementation was executed in a phased architecture to reduce risk, first replatforming Netezza tables and Data Stage source and target bindings to Amazon Redshift, then stabilizing the Redshift table environment before converting ETL jobs from Data Stage to Talend. The Amazon Redshift deployment served as the central Data Warehouse repository for HCP and HCO customer information, supporting Customer Master processing and totem pole mastering logic changes required by new vendor data feeds. Integrations and interfaces documented in the program included IBM Initiate for master data management, IBM Data Stage as the incumbent ETL, Netezza as the prior database platform, Oracle sources, Talend as the target ETL runtime, Erwin for data modeling, and AWS infrastructure components. Approximately 60 vendor supplied files were audited and reengineered into new ingestion pipelines feeding the MDM Hub, with source to target mappings updated to reflect the new vendor hierarchy for Health Care Provider and Health Care Organization records. Governance and process restructuring included an end to end data lineage and ETL job lineage capability that enabled impact analysis and traceability, a formal data profiling methodology to gate incoming files, and updated totem pole logic in the MDM Hub for Customer Master resolution. Deliverables included high level and detailed specifications, user stories, use cases, logical and physical models created in Erwin, process flow diagrams and data mapping, all socialized with business and technical stakeholders to align enterprise standards. Operational controls applied strong data privacy safeguards for HCO and HCP information, applying HIPPA rules and other regulatory considerations across ingestion and mastering processes. The program identified gaps in prior ETL best practices, provided documented remediation approaches, and delivered a staged migration path that separated infrastructure replatforming from ETL conversion to limit disruption to business and IT operations. | |
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Life Sciences | 28000 | $33.4B | United States | Amazon Web Services (AWS) | Amazon Redshift | Data Warehouse | 2020 | n/a |
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Life Sciences | 55000 | $56.3B | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2019 | n/a |
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Life Sciences | 6100 | $1.5B | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2019 | n/a |
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Life Sciences | 138100 | $88.8B | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2018 | n/a |
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Life Sciences | 60000 | $14.8B | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2018 | n/a |
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Life Sciences | 13539 | $27.0B | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2012 | n/a |
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Life Sciences | 500 | $100M | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2016 | n/a |
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Life Sciences | 81000 | $63.6B | United States | IBM | IBM Netezza Data Warehouse | Data Warehouse | 2019 | n/a |
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