DP-201T01 Designing an Azure Data Solution
6/14/2021 - 6/15/2021COURSE LENGTH:
9:00am - 4:30pm
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.
AUDIENCE AND PREREQUISITES
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.
The audience for this course is 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 is individuals who develop applications that deliver content from the data platform technologies that exist on Microsoft Azure.
Course cost listed does not include the cost of courseware. Course is subject to a minimum enrollment to run. Course may run virtually as a Virtual Instructor-Led (VILT) class if minimum enrollment is not met. For more information, please contact: email@example.com or call 207-775-0244
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 Case Study Lab : Case StudyModule 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 AzureModule 3: Azure Real-Time Reference Architectures Lambda architectures for a Real-Time Perspective Architect a stream processing pipeline with Azure Stream Analytics Design a stream processing pipeline with Azure Databricks Create an Azure IoT reference architecture Lab : Azure Real-Time Reference ArchitecturesModule 4: Data Platform Security Design Considerations Defense in Depth Security Approach Identity Management Infrastructure Protection Encryption Usage Network Level Protection Application Security Lab : Data Platform Security Design ConsiderationsModule 5: Designing for Resiliency and Scale Adjust Workload Capacity by Scaling Optimize Network Performance Design for Optimized Storage and Database Performance Identifying Performance Bottlenecks Design a Highly Available Solution Incorporate Disaster Recovery into Architectures Design Backup and Restore strategies Lab : Designing for Resiliency and ScaleModule 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