Course DP-201T01 Designing an Azure Data Solution | nt.ua

Course DP-201T01 Designing an Azure Data Solution

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.


After completing this course, students will be able to:
  • Design with Security in mind;
  • Consider performance and scalability;
  • Design for availability and recoverability;
  • Design for efficiency and operations;
  • Core Principles of Creating Architectures;
  • Describe 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;
  • Case study;
  • Lambda architectures for a Real-Time Mode Perspective;
  • Architect a stream processing pipeline with Azure Stream Analytics;
  • Design a stream processing pipeline with Azure Databricks;
  • Create an Azure IoT reference architecture;
  • Defense in Depth Security Approach;
  • Identity Management;
  • Infrastructure Protection;
  • Encryption Usage;
  • Network Level Protection;
  • Application Security;
  • 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;
  • Maximize the Efficiency of your Cloud Environment;
  • Use Monitoring and Analytics to Gain Operational Insights;
  • Use Automation to Reduce Effort and Error.
Audience Profile

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.


Before attending this course, students must have:

In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses:

  • Azure fundamentals
  • DP-200: Implementing an Azure Data Solution
  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
  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
  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
  4. Data Platform Security Design Considerations
    • Defense in Depth Security Approach
    • Identity Management
    • Infrastructure Protection
    • Encryption Usage
    • Network Level Protection
    • Application Security
  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
  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

Sign up for the closest date

Course Code

DP-201T01

Exam Code

DP-201

Length, days (hours)

2 (16)

Closest dates

Price, UAH

Class schedule

Date

Time

12.11.20
09:30 - 17:00
13.11.20
09:30 - 17:00