Masterclass: Secure Data Engineering in the Azure Cloud
In the modern world, every organization relies on data more every day. Businesses tend to deal with large amount of data which could be spread across various sources and to effectively analyze it – it is crucial to consolidate it into one key location. The modern era posed us with many challenges – especially in the Data sector as it is getting harder to connect all the dots together. Microsoft’s Azure Cloud is a great solution that makes it easier to manage and analyze the data that we deal with across various sources.
This intense hands-on training if perfect for anyone that has experience with Windows Servers, SQL Servers and deals with or is interested in data management and analysis. During the training, you will gain hands-on experience on how to choose and work with the compute and storage options for data engineering workloads, deep-dive into Azure Data Lake and Databricks. Moreover, you will also go through the key aspects of Azure Synapse Analytics and you will have the chance to become the master of Hybrid Transactional Analytical Processing. By the end of the training you will also gain practical knowledge on data transformation and data movement orchestration using Azure Data Factory and Realtime stream processing!
The training is though and authored by one of the best Experts in the data field – Microsoft’s Data Platform MVP Damian Widera.
The course is an intense workshop! During these 3 days we recommend a good cup of coffee – this course is really intense and in order not to miss a thing you MUST stay awake!
Virtual Learning
This interactive training can be taken from any location, your office or home and is delivered by a trainer. This training does not have any delegates in the class with the instructor, since all delegates are virtually connected. Virtual delegates do not travel to this course, Global Knowledge will send you all the information needed before the start of the course and you can test the logins.
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- Delivery Format: Virtual Learning
- Date 25-27 November, 2026 | 9:00 AM to 5:00 PM
- Location: Virtual (W. Europe )
- Language: English
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