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Journey to Cloud and Cloud optimization

A joint webinar by SMT Data and Zangenberg Analytics

Target Group:

The webinar is targeted:

  • Contract management/procurement,
  • IT Finance,
  • Technical personnel responsible for following up on server capacity and related costs
  • Application owners,
  • IT Infrastructure owners
  • IT Development
  • IT Architects
  • IT Operations


Part 1: Optimizing your Journey to Cloud, by Frederik Bastkær Christensen from Zangenberg Analytics

  • What is needed to cost-efficiently move to the Cloud
  • What is the optimization potential from moving to AWS, Azure or Google for IaaS and PaaS services?
  • How to mitigate the budgeting and management challenges facing organizations adopting cloud
  • Learnings from structuring the governance surrounding the largest Nordic IaaS and PaaS adopters
  • How to predict the Cloud costs for moving existing or new applications to a IaaS or PaaS environment
  • Do’s and don’ts when adopting IoT, Data lakes, Kubernetes, Apps and DBaaS in Azure and AWS
  • Cloud checklist and governance input for getting started on a more managed Cloud adoption journey

Part 2: Cloud readiness and Cloud optimization, by Steven Thomas from SMT Data

  • The case for cloud optimization: Why can costs get out of hand in the cloud?
  • Cloud providers’ reporting versus what you really need to know
  • The pitfalls of cloud capacity management
  • Getting in control
  • Understanding the costs in technical terms
  • Understanding the costs in business terms
  • Making it happen

Practical information

The webinar will be in English. At the end of the webinar there will be an interactive Q&A session.

As a participant you are required to register in advance. To ensure GDPR compliance we will need your consent to allow for other participants to be able to see your name and email during the session, as we are making use of Microsoft Teams.

For any question please do not hesitate to contact us at: marketing@smtdata.com

Registration - Journey to Cloud and Cloud optimization

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