Designing an Azure Data Solution (DP-201) Duration: 2 days Teaching method: classroom live and virtual classroom In this course, the students will design various data platform technologies into solutions that are in line with business and technical requirements. This can include on-premises, cloud, and hybrid data scenarios which incorporate relational, No-SQL or Data Warehouse data. They will also learn how to design process architectures using a range of technologies for both streaming and batch data. The students will also explore how to design data security including data access, data policies and standards. They will also design Azure data solutions which includes the optimization, availability and disaster recovery of big data, batch processing and streaming data solutions. OBJECTIVES Rampup in order to pass for for exam DP-201 ‘Desiging an Azure Data Solution’. When already passed for exam DP-200 ‘Implementing an Azure Data Solution’, you’ll receive the certificate Microsoft Certified: Azure Data Engineer Associate. AUDIENCE The primary audience for this course are data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure. The secondary audience for this course are individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure. PREREQUISITES Implementing an Azure Data Solution (DP-200) or comparable knowledge Microsoft Azure Fundamentals (AZ-900) or comparable knowledge. The primary audience for this course are data professionals, data architects, and business intelligence professionals who want to learn about the data platform technologies that exist on Microsoft Azure. The secondary audience for this course are individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure. TOPICS Module 1: Data Platform Architecture Considerations Core Principles of Creating Architectures Design with Security in Mind Performance and Scalability Design for availability and recoverability Design for efficiency and operations Lab : Case Study Module 2: Azure Batch Processing Reference Architectures Lambda architectures from a Batch Mode Perspective Design an Enterprise BI solution in Azure Automate enterprise BI solutions in Azure Architect an Enterprise-grade Conversational Bot in Azure Lab : Architect an Enterprise-grade Conversational Bot in Azure Module 3: Azure Real-Time Reference Architectures Lambda architectures for a Real-Time Perspective Lambda architectures for a Real-Time Perspective Design a stream processing pipeline with Azure Databricks Create an Azure IoT reference architecture Lab : Azure Real-Time Reference Architectures Module 4: Data Platform Security Design Considerations Defense in Depth Security Approach Network Level Protection Identity Protection Encryption Usage Advanced Threat Protection Lab : Data Platform Security Design Considerations Module 5: Designing for Resiliency and Scale Design Backup and Restore strategies Optimize Network Performance Design for Optimized Storage and Database Performance Design for Optimized Storage and Database Performance Incorporate Disaster Recovery into Architectures Design Backup and Restore strategies Lab : Designing for Resiliency and Scale Module 6: Design for Efficiency and Operations Maximizing the Efficiency of your Cloud Environment Use Monitoring and Analytics to Gain Operational Insights Use Automation to Reduce Effort and Error Lab : Design for Efficiency and Operations SCHEDULE Contact Gelieve dit veld leeg te laten.Send