Microsoft Certified: Azure Data Engineer Associate (DP200-201)

This five-day course is aligned to Azure Exams Implementing an Azure Data Solution and Designing an Azure Data Solution. It contains courseware that helps prepare students for Exams DP-200 and DP-201. Passing these two exams is required to earn the Microsoft Certified: Azure Data Engineer Associate certification.

Pohađajte naše zvanične Microsoft obuke u Beogradu, putem virtuelne učionice (online, uživo) ili u vašim prostorijama (on-site).

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Termini obuke

Beograd
Planirani datumPlanirani datum
08.06.2020
625€
 
Srpski
Novi Sad
Planirani datumPlanirani datum
08.06.2020
625€
 
Srpski
Virtuelna učionica
Planirani datumPlanirani datum
08.06.2020
530€
 
Srpski
Beograd
Planirani datumPlanirani datum
14.09.2020
625€
 
Srpski
Novi Sad
Planirani datumPlanirani datum
14.09.2020
625€
 
Srpski
Virtuelna učionica
Planirani datumPlanirani datum
14.09.2020
530€
 
Srpski
530€
Trajanje obuke: 
5 dana / 35 sati

Privatni trening

On-site / Online
Minimalan broj polaznika: 3
5 dana / 35 sati
Cena na zahtev
srpski ili engleski
Plan obuke: 

Implementing an Azure Data Solution (DP-200T01)

Module 1: Azure for the Data Engineer

This module explores how the world of data has evolved and how cloud data platform technologies are providing new opportunities for business to explore their data in different ways. The student will gain an overview of the various data platform technologies that are available, and how a Data Engineers role and responsibilities has evolved to work in this new world to an organization benefit

  • Explain the evolving world of data
  • Survey the services in the Azure Data Platform
  • Identify the tasks that are performed by a Data Engineer
  • Describe the use cases for the cloud in a Case Study

Module 2: Working with Data Storage

This module teaches the variety of ways to store data in Azure. The Student will learn the basics of storage management in Azure, how to create a Storage Account, and how to choose the right model for the data you want to store in the cloud. They will also understand how data lake storage can be created to support a wide variety of big data analytics solutions with minimal effort.

  • Choose a data storage approach in Azure
  • Create an Azure Storage Account
  • Explain Azure Data Lake storage
  • Upload data into Azure Data Lake

Module 3: Enabling Team Based Data Science with Azure Databricks

This module introduces students to Azure Databricks and how a Data Engineer works with it to enable an organization to perform Team Data Science projects. They will learn the fundamentals of Azure Databricks and Apache Spark notebooks; how to provision the service and workspaces and learn how to perform data preparation task that can contribute to the data science project.

  • Explain Azure Databricks
  • Work with Azure Databricks
  • Read data with Azure Databricks
  • Perform transformations with Azure Databricks

Module 4: Building Globally Distributed Databases with Cosmos DB

In this module, students will learn how to work with NoSQL data using Azure Cosmos DB. They will learn how to provision the service, and how they can load and interrogate data in the service using Visual Studio Code extensions, and the Azure Cosmos DB .NET Core SDK. They will also learn how to configure the availability options so that users are able to access the data from anywhere in the world.

  • Create an Azure Cosmos DB database built to scale
  • Insert and query data in your Azure Cosmos DB database
  • Build a .NET Core app for Cosmos DB in Visual Studio Code
  • Distribute your data globally with Azure Cosmos DB

Module 5: Working with Relational Data Stores in the Cloud

In this module, students will explore the Azure relational data platform options including SQL Database and SQL Data Warehouse. The student will be able explain why they would choose one service over another, and how to provision, connect and manage each of the services.

  • Use Azure SQL Database
  • Describe Azure SQL Data Warehouse
  • Creating and Querying an Azure SQL Data Warehouse
  • Use PolyBase to Load Data into Azure SQL Data Warehouse

Module 6: Performing Real-Time Analytics with Stream Analytics

In this module, students will learn the concepts of event processing and streaming data and how this applies to Events Hubs and Azure Stream Analytics. The students will then set up a stream analytics job to stream data and learn how to query the incoming data to perform analysis of the data. Finally, you will learn how to manage and monitor running jobs.

  • Explain data streams and event processing
  • Data Ingestion with Event Hubs
  • Processing Data with Stream Analytics Jobs

Module 7: Orchestrating Data Movement with Azure Data Factory

In this module, students will learn how Azure Data factory can be used to orchestrate the data movement and transformation from a wide range of data platform technologies. They will be able to explain the capabilities of the technology and be able to set up an end to end data pipeline that ingests and transforms data.

  • Explain how Azure Data Factory works
  • Azure Data Factory Components
  • Azure Data Factory and Databricks

Module 8: Securing Azure Data Platforms

In this module, students will learn how Azure provides a multi-layered security model to protect your data. The students will explore how security can range from setting up secure networks and access keys, to defining permission through to monitoring across a range of data stores.

  • An introduction to security
  • Key security components
  • Securing Storage Accounts and Data Lake Storage
  • Securing Data Stores
  • Securing Streaming Data

Module 9: Monitoring and Troubleshooting Data Storage and Processing

In this module, the student will get an overview of the range of monitoring capabilities that are available to provide operational support should there be issue with a data platform architecture. They will explore the common data storage and data processing issues. Finally, disaster recovery options are revealed to ensure business continuity.

  • Explain the monitoring capabilities that are available
  • Troubleshoot common data storage issues
  • Troubleshoot common data processing issues
  • Manage disaster recovery

Designing an Azure Data Solution (DP-201T01)

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 your architecture regardless of technology choice, can help you design, build, and continuously improve your architecture for an organizations benefit.

  • 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

Module 2: Azure Batch Processing Reference Architectures

In this module, the student 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 student will also be exposed to an AI architecture and how the data platform can integrate with an AI solution.

  • 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

Module 3: Azure Real-Time Reference Architectures

In this module, the student 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 the 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.

  • 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

Module 4: Data Platform Security Design Considerations

In this module, the student will learn how to incorporate security into an architecture design and learn the key decision points in Azure provides to help you create a secure environment through all the layers of your architecture.

  • Defense in Depth Security Approach
  • Identity Management
  • Infrastructure Protection
  • Encryption Usage
  • Network Level Protection
  • Application Security

Module 5: Designing for Resiliency and Scale

In this module, student will learn scaling services to handle load. They will learn how identifying network bottlenecks and optimizing your storage performance are important to ensure your 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 your architecture.

  • 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

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, they will understand how to design architectures that eliminates waste and gives them full visibility into what is being utilized in your organizations Azure environment.

  • Maximizing the Efficiency of your Cloud Environment
  • Use Monitoring and Analytics to Gain Operational Insights
  • Use Automation to Reduce Effort and Error
Benefiti: 
  • Video snimak predavanja u periodu od 365 dana posle kraja obuke

  • Pristup laboratorijama putem Interneta 180 dana od kraja obuke
  • Materijal u elektronskom obliku

  • Zvaničan Microsoft sertifikat o pohađanju kursa

Poželjno predznanje: 

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

O sertifikaciji: 

Ispit:

  • Priprema za Microsoft Certified: Azure Data Engineer Associate sertifikaciju
  • Šifra ispita: DP-200 i DP-201
  • Cena: 80 USD svaki
  • Struktura ispita
    • Implement data storage solutions
    • Manage and develop data processing 
    • Monitor and optimize data solutions
    • Design Azure data storage solutions 
    • Design data processing solutions 
    • Design for data security and compliance
  • Svi detalji...