Building an Intelligent Data Platform using Azure DevOps

English Advanced DEVOPS

This session will explore best practices for building a cloud-scale analytics platform on data landing zones in Azure. We will delve into the Infrastructure as Code (IaC) in DevOps, and how it can help automate the platform build process. We will also discuss the key considerations for designing a data platform: storage, processing, access, and security. Furthermore, we will discuss the benefits of using Azure Synapse for large-scale analytics, including serverless SQL pools and integrated Power BI reporting. We will demonstrate how to use Azure Synapse Studio to manage and monitor your analytics workloads, and how to optimize your data platform for cost, performance, and security.


Marian Dumitru Danci

Data Platform Engineer at Ascent

For the last 3 years, I have been building and maintaining data platforms such as RStudio Enterprise, Qlik Sense and Microsoft Intelligent Data Platform of all sizes. From RStudio platforms with 2000 users at international companies to proof of concepts for small teams with limited data literacy skills. I am certified as a DevOps Expert, Azure Admin and some other Microsoft certificates, alongside of IaC tools such as Terraform and Ansible. Because I work between different expertise areas: Cloud, Data Engineering, Data Science and DevOps, this has provided me with a well-rounded and insightful outlook on diverse perspectives.

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