Microsoft Official Courses (MOC)
Course DP-201T01-A: Designing an Azure Data Solution
За Курса (About this Course):
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, NoSQL, 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.
Цели – Какво ще научите (Course Goals/Skills):
- Describe data warehouse concepts and architecture considerations.
- Select an appropriate hardware platform for a data warehouse.
- Design and implement a data warehouse.
- Implement Data Flow in an SSIS Package.
- Implement Control Flow in an SSIS Package.
- Debug and Troubleshoot SSIS packages.
- Implement an ETL solution that supports incremental data extraction.
- Implement an ETL solution that supports incremental data loading.
- Implement data cleansing by using Microsoft Data Quality Services.
- Implement Master Data Services to enforce data integrity.
- Extend SSIS with custom scripts and components.
- Deploy and Configure SSIS packages.
- Describe how BI solutions can consume data from the data warehouse.
Курсът е предназначен за (Audience):
- 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.
Формат на курса
Език на курса (Course Language Option)
Може да изберете Език на който да се проведе обучението – български или английски. Всичките ни инструктори владеят свободно английски език.
Учебни Метериали: в електронен формат (Учебните материали са на английски), включени в цената с неограничен достъп.
Лабораторна среда: всеки курсист разполага със собствена лаб среда, където се провеждат упражненията, част от курса.
- 2 работни дни (09:00 – 17:00)
- 16 уч.ч. обучение (теория и практика) в извънработно време с продължителност 2 седмици
- събота и неделя 10:00 – 14:00, 14:00 – 18:00, 18:00 – 22:00
- понеделник и сряда 19:00 – 23:00
- вторник и четвъртък 19:00 – 23:00
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Предпоставки (Изисквания) за Участие (Prerequisites):
In addition to their professional experience, students who take this training should have technical knowledge equivalent to the following courses:
Курсът подготвя за следните сертификационни нива
Exam DP-201: Designing an Azure Data Solution
- Може да се сертифицирате в нашия тест център с ваучер с отстъпка от цената на изпит.
Module 1: Data Platform Architecture Considerations
In this module, the students will learn how to design and build secure, scalable, and performant solutions in Azure by examining the core principles found in every good architecture. They will learn how using key principles throughout architecture, regardless of technology choice, can help you design, build, and continuously improve the architecture for an organization's benefit.
Module 2: Azure Batch Processing Reference Architectures
In this module, students will learn the reference design and architecture patterns for dealing with the batch processing of data. The student will be exposed to dealing with the movement of data from on-premises systems into a cloud data warehouse and how it can be automated. The students will also be exposed to an AI architecture and how the data platform can integrate with an AI solution.
Module 3: Azure Real-Time Reference Architectures
In this module, the students will learn the reference design and architecture patterns for dealing with streaming data. They will learn how streaming data can be ingested by Event Hubs and Stream Analytics to deliver real-time analysis of data. They will also explore a data science architecture that streams data into Azure Databricks to perform trend analysis. They will finally learn how an Internet of Things (IoT) architecture will require data platform technologies to store data.
Module 4: Data Platform Security Design Considerations
In this module, the students will learn how to incorporate security into an architecture design and learn the key decision points in Azure provided to help create a secure environment through all the layers of architecture.
Module 5: Designing for Resiliency and Scale
In this module, students will learn scaling services to handle load. They will learn how identifying network bottlenecks and optimizing storage performance are important to ensure users have the best experience. They will also learn how to handle infrastructure and service failure, recover from the loss of data, and recover from a disaster by designing availability and recoverability into the architecture.
- Adjust Workload Capacity by Scaling
- Optimize Network Performance
- Design for Optimized Storage and Database Performance
- Identify Performance Bottlenecks
- Design a Highly Available Solution
- Incorporate Disaster Recovery into Architectures
- Design Backup and Restore strategies
- Lab : Designing for Resiliency and Scale
Module 6: Design for Efficiency and Operations
In this module, students will learn how to design an Azure architecture that is operationally-efficient and minimizes costs by reducing spend and they will understand how to design architectures that eliminate waste and gives them full visibility into what is being utilized in the organization's Azure environment.