Real-World Case Studies and Customer Success Stories with Striim

Macy's, a leading American department store, faced challenges with data inconsistencies, high maintenance costs, and slow speed to market. They partnered with... Striim and Google Cloud to modernize their platform. Striim's real-time data integration helped Macy's streamline operations and enhance customer experiences. This collaboration led to operational excellence and cost savings for Macy's.
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Morrisons, a leading UK food retailer, needed to modernize its data infrastructure to improve customer experience and operational efficiency. They transitioned to... Google Cloud with Looker for better reporting and used Striim to connect systems and ingest data into Google BigQuery. This integration provided real-time visibility into stock levels and improved inventory management. As a result, Morrisons enhanced on-shelf availability, increased online picking efficiency, and empowered staff with real-time data, supporting a data-driven culture for growth.
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Macy's faced challenges with data inconsistencies and high costs due to outdated systems. They needed a single source of truth... for their databases. Striim provided a real-time data integration platform, replicating data to Google Cloud services. This ensured consistent customer experiences and efficient inventory management. Macy's reduced costs by moving from mainframe systems to Google Cloud, improving operational efficiency and customer satisfaction.
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Striim helped Clover solve problems with fragmented data and slow manual processes. Clover had over 12 years of data in... 23 MySQL databases and thousands of tables. This made it hard to get real-time insights and slowed business growth. Striim provided a scalable, automated data integration solution. Clover can now deliver real-time insights to merchants and support global payment processing more efficiently.
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A major global financial data provider faced challenges with data distributed across 80 siloed systems, leading to high costs and slow innovation. To address this,... they adopted a cloud-first strategy, aiming to migrate newer systems to the cloud and rebuild legacy systems as cloud-native applications. The company needed to move 50 billion records and 40,000 corporate customers while minimizing disruption. They used Striim to ensure data availability and flexibility during a three-year cloud migration and data modernization process.
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MineralTree needed to provide real-time invoicing reports to customers, but their old data system was slow and inefficient. They faced challenges... in replicating data and providing visualizations. By using Striim's real-time data streaming with Snowflake, dbt, and Looker, they modernized their data infrastructure. This allowed them to offer on-demand invoicing insights and faster feature deployment, improving customer experience with real-time data flows.
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Striim helped CityFibre upgrade its data infrastructure for real-time integration. CityFibre needed to handle more data as it grew and... partnered with Sky. Old tools like Salesforce and Kafka native could not keep up. Striim replaced these, enabling fast, reliable data flow from Oracle, Salesforce, and Kafka into Snowflake. This gave CityFibre a stable, scalable, and API-first data platform to support its rapid expansion.
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Ciena, a networking systems company, needed to improve their data and analytics ecosystem. They wanted to reduce the time it... took to replicate and aggregate data from multiple systems. Ciena chose Striim to stream data from operational systems to Snowflake in near real-time. This solution allowed them to replicate changes from Oracle at scale without disrupting business operations.
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UPS Capital faced challenges with package theft and data management due to increased online shopping. They needed a solution for... real-time data processing to improve risk management. UPS Capital used Striim's real-time data streaming and Google BigQuery's analytics to enhance delivery security. This integration allowed for immediate data ingestion and real-time risk assessments. The DeliveryDefenseTM system improved predictive accuracy for delivery locations. As a result, UPS Capital improved customer experience, reduced costs, and enhanced data processing and analytical accuracy.
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Virgin Media O2 used Striim to build its Instant Network for real-time customer experiences. The company faced challenges with siloed... systems and slow, batch-based processing after a major merger. Striim provided real-time data integration, enabling faster insights and AI-driven automation. This improved network management, personalization, and operational efficiency. Virgin Media O2 now delivers more reliable connectivity and better customer service across the UK.
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A leading supply chain technology provider needed to move a key SaaS application to the cloud to increase scalability and resilience. They faced the... challenge of migrating a 1TB on-premises Oracle Database to Google Cloud Platform. The company used Striim to ensure fast, reliable, and accurate data migration. This helped them replace manual processes with a cloud-based solution, improving visibility and optimization in logistics.
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A nonprofit educational healthcare organization needed to migrate its student information system to Azure SQL Server. They faced challenges with... performance and API data capture. Striim provided a solution with real-time data integration and streaming. This allowed seamless data synchronization between cloud and on-premise systems. The results included real-time data access, improved response time, increased student conversion, and seamless integration of critical systems.
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The General Medical Council (GMC) wanted to modernize its analytics capabilities. They faced challenges with legacy systems that limited scalability... and slowed innovation. GMC chose Striim to stream real-time data from on-premise systems to Azure cloud. This solution reduced costs by eliminating expensive tools and improved operational efficiency by reducing data latency. Striim enabled a modernized data pipeline for real-time readiness.
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Kramp, a leading distributor in the agricultural sector, wanted to improve its data management system. They aimed to move their... data warehouse to a cloud-based infrastructure on Google Cloud Platform for better decision-making and efficiency. Kramp faced challenges with their legacy data migration solution, which required high maintenance and affected data quality. They chose Striim for real-time data analytics to overcome these issues and enhance operational efficiencies.
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Kramp wanted to improve decision-making and efficiency by using near real-time analytics. They moved from traditional data warehousing to a... cloud-based system on Google Cloud Platform. Their old data migration solution had issues with product maturity and maintenance, affecting data quality. Kramp chose Striim for real-time data integration, connecting databases like Oracle and Microsoft. This improved data replication for forecasting and order management. Striim's platform helped Kramp enhance machine learning projects and data analysis. Real-time updates on order status improved customer communication and satisfaction, reducing customer service calls.
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American Airlines needed to manage massive amounts of real-time data to support over 5,800 flights daily. They partnered with Microsoft... Azure to modernize operations and analytics. The TechOps team deployed a real-time data hub using MongoDB, Striim, Azure, and Databricks. This setup allowed them to process and model data in real-time, improving operational efficiency. Within 12 weeks, they achieved digital transformation, enhancing the travel experience for customers.
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Discovery Health had issues with data processing delays, taking 24 hours to process data. This affected their efficiency and customer... experience. They needed real-time data processing. Striim's Change Data Capture technology helped them integrate systems and cut data processing time to seconds. This improved decision-making and customer experiences. They saved on operational costs and improved health outcomes by using real-time data for personalized engagement and predictive analytics.
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