Mihai Tataran Webinar

Title: End to end strategy on the Microsoft Cloud

Speaker: Mihai Tataran, GM @Avaelgo, Microsoft RD and MVP

Date and Time: Thu, Oct 17, 2019 1:00 PM – 2:00 PM CEST

Webinar Description:
In this webinar we will discuss how to design a 5 step strategy around the Cloud with examples on Microsoft technologies, mainly Azure and Microsoft 365.
We will explore these aspects in a very broad but down to earth conversation:
1). Designing the strategy;
2). Migrate to the Cloud;
3). Optimize the Cloud;
4). Support for Cloud;
5). Empower with the Cloud.

Key benefit of attending:
– Understand the key challenges with the Cloud, and many examples from real life projects.

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Thorsten Hans Webinar

Title: Code your Azure Deployments using Terraform

Speaker: Thorsten Hans, MVP, Thinktecture AG, Germany 

Date and Time: Fri, Oct 18, 2019 11:00 AM – 12:00 PM CEST

Webinar Description:
Using HashiCorp’s Terraform you can code almost every Azure Deployment. Having your entire infrastructure as source code makes it easy to spin up new environments in a couple of minutes. Terraform takes this approach a step further, having a single language and a single CLI allows you to describe deployments for almost every cloud vendor. With Terraform Execution Plans you can also inspect what will be deployed, changed or deleted in Azure without harming existing deployments. Join this talk by Thorsten Hans and learn how to write your deployments and quickly create different, independent environments such as Testing, Staging, and Production in Azure. 

Key benefits of attending:
– Get started with HashiCorps Terraform to automate and code Azure Deployments 
– Learn about Azure Deployment Automation 
– Discover Terraform and Infrastructure as Code 

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Edward Watson Webinar

Title: 6 Reasons for Microsoft Office 365 Backup

Speaker: Edward Watson, Global Product Marketing Manager, Veeam Software, USA 

Date and Time: Thu, Oct 24, 2019 3:00 PM – 4:00 PM CEST

Webinar Description:
Microsoft Office 365 fits the needs of many organizations, providing application Availability and uptime for users. But when it comes to protecting your Office 365 data, it can be unclear what part of your environment you are responsible for protecting. Ultimately, you need to ensure that you have access to and control over your Exchange, SharePoint and OneDrive for Business data. This insightful webinar with Veeam® will explore 6 critical reasons for Office 365 data protection, and make it clear what falls on your organization to protect. 

Key benefits of attending:
– Understand the difference between Microsoft’s responsibility for Office 365 and your responsibility. 
– Find out 6 reasons why backing up Office 365 is critical. 
– Learn what you need to be in complete control of your Office 365 data. 

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Stefano Tempesta Webinar

Title: Secure Multiparty Machine Learning with Azure Confidential Computing

Speaker: Stefano Tempesta, Microsoft RD (Regional Director) and MVP, Avanade, UK 

Date and Time: Tue, Dec 17, 2019 11:00 AM – 12:00 PM CET

Preserving privacy when processing data from multiple sources with machine learning is always a challenge. Organisations may want to perform collaborative data analytics while guaranteeing the privacy of their individual datasets. Combining multiple data sources to support a better algorithmic outcome improves accuracy of prediction, but it may come at a cost to confidentiality, if sensitive information is not accurately protected. 

Azure Confidential Computing adds new data security capabilities to the cloud and specifically to machine learning processing. By using trusted execution environments (TEEs) to protect your data while in use, with confidential computing, you can use machine learning algorithms across different organisations to better train models, without revealing the processed data. 

In this webinar, Stefano Tempesta, Microsoft Regional Director and MVP on AI and Business Applications, will present the benefits of Azure Confidential Computing in an ML scenario, where two separate health institutes collaborate on data analysis and prediction using Azure Machine Learning, and still mask any sensitive information to protect the privacy of their patients. 

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