Whitepaper Archive | October 2021

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October 29th
- Explaining the UK’s supply chain crisis
October 27th
- Mobile order and Pay at Table
- Technology and tactics to support your hospitality business
- Driving adoption of digital self-service
- Pay at table best practices
October 18th
- Comparing serverless and server-based technologies
- Build mobile and web apps faster
- Best practices for running Microsoft SQL Server on AWS
October 15th
- Build trustworthy AI with MLOps
- The business value of MLOps
- The AI-powered supply chain
- Next-generation time series: Forecasting for the real world, not the ideal world
- Trusted AI: A guide to building fair and unbiased AI systems
- AI in customer analytics
October 13th
- The future of productivity
- Digital remote monitoring and dispatch services’ impact on edge computing and data centres
October 12th
- A quantitative comparison of UPS monitoring and servicing approaches across edge environments
October 8th
- Going solo: What happens next after becoming your own boss?
- High-performance persistent storage for virtualised workloads
- The business value of Red Hat Runtimes
- Service mesh or API management?
- Building a cloud-native, hybrid-multi cloud infrastructure
October 7th
- The event mesh: A primer
- The business value of Red Hat OpenShift
- 97 things every cloud engineer should know
- 2021 Thales access management index: European edition
- 2021 Thales access management index: Global edition
- Shining light on new 'cool' cloud technologies and their drawbacks
October 5th
- Seven tips to prepare for your return-to-office
- Three tips for leading hybrid teams effectively
- Seven steps to connect and empower your frontline workers
- IDC agility assessment
- ITSM workflow handbook: No more "If only IT could do X"
- The human experience of IT service management
- Five best practices for resilient, reliable, remote IT services
- From broken to boundless
October 4th
- Seven leading machine learning use cases
October 1st
- The best defence against ransomware
- How to manage AI risk