DP-200: Implementing an Azure Data Solution 

În acest curs, studenții vor implementa diverse tehnologii ale platformelor de date în soluții care sunt în conformitate cu cerințele  business și tehnice, inclusiv scenarii de date locale, cloud și hibride care includ atât date relaționale, cât și date NoSQL.

Cui i se adresează?

Acest curs de adresează Data Professionals, Data Architects și Business Intelligence Professionals care vor să învețe despre tehnologiile platformelor de date care există în Microsoft Azure. Acest training se adresează și unui public secundar și anume persoanelor care dezvolta aplicații care livrează conținut din datele platformei tehnologiilor care există in Microsoft Azure.

Ce veți învăța?

Cursanții vor învăța cum să proceseze date folosind o serie de tehnologii și limbaje, atât pentru fluxuri, cât și pentru date de lor.
Studenții vor explora, de asemenea, modul de implementare a securității datelor, inclusiv autentificarea, autorizarea, politicile de date și standardele. De asemenea, aceștia vor defini și implementa monitorizarea soluțiilor de date pentru stocarea datelor, cât și pentru activitățile de prelucrare a datelor. În cele din urmă, vor gestiona și depana soluții de date Azure care includ optimizarea și recuperarea datelor în caz de dezastre, procesarea loturilor și a fluxurilor de date.

Cerințe preliminare:

Pe lângă experiența profesională, studenții care parcurg acest curs ar trebui să aibă cunoștințe tehnice echivalente următorului curs: Azure Fundamentals.

Agenda cursului:

Materialele de curs sunt în limba Engleză. Predarea se face în limba Română.

Citește agenda cursului
Citește agenda cursului

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 businesses to explore their data in different ways. The students will gain an overview of the various data platform technologies that are available and how a Data Engineer’s role and responsibilities has evolved to work in this new world to an organization’s benefit.

Lessons

  • 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

Lab : Azure for the Data Engineer

  • Identify the evolving world of data
  • Determine the Azure Data Platform Services
  • Identify tasks to be performed by a Data Engineer
  • Finalize the data engineering deliverables

After completing this module, students will be able to:

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 students 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 want to be stored 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.

Lessons

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

Lab : Working with Data Storage

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

After completing this module, students will be able to:

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 how to perform data preparation task that can contribute to the data science project.

Lessons

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

Lab : Enabling Team Based Data Science with Azure Databricks

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

After completing this module, students will be able to:

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, 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.

Lessons

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 data globally with Azure Cosmos DB

Lab : Building Globally Distributed Databases with Cosmos DB

Create an Azure Cosmos DB
Insert and query data in Azure Cosmos DB
Build a .Net Core App for Azure Cosmos DB using VS Code
Distribute data globally with Azure Cosmos DB

After completing this module, students will be able to:

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 Azure Cosmos DB in Visual Studio Code
Distribute 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 students will be able explain why they would choose one service over another, and how to provision, connect, and manage each of the services.

Lessons

  • 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

Lab : Working with Relational Data Stores in the Cloud

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

After completing this module, students will be able to:

Use Azure SQL Database
Describe Azure Data Warehouse
Create and Query 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, they will learn how to manage and monitor running jobs.

Lessons

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

Lab : Performing Real-Time Analytics with Stream Analytics

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

After completing this module, students will:

Be able to explain data streams and event processing
Understand Data Ingestion with Event Hubs
Understand 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.

Lessons

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

Lab : Orchestrating Data Movement with Azure Data Factory

Explain how Data Factory Works
Azure Data Factory Components
Azure Data Factory and Databricks

After completing this module, students will:

Understand Azure Data Factory and Databricks
Understand Azure Data Factory Components
Be able to explain how Azure Data Factory works

Module 8: Securing Azure Data Platforms

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

Lessons

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

Lab : Securing Azure Data Platforms

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

After completing this module, students will:

Have an introduction to security
Understand key security components
Understand securing Storage Accounts and Data Lake Storage
Understand securing Data Stores
Understand securing Streaming Data

Module 9: Monitoring and Troubleshooting Data Storage and Processing

In this module, the students 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.

Lessons

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

Lab : Monitoring and Troubleshooting Data Storage and Processing

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

After completing this module, students will be able to:

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

Este recomandat să continui cu:
Programe de certificare

Acest curs îi pregătește pe studenți pentru susținerea examenului Microsoft DP-200.

Detalii curs

Durată
3
zile

Preț
570
EUR

Modalități de livrare
Predare în clasă, Clasă hibridă, Clasă virtuală
Nivel de specializare
2. Fundamental
Într-o economie bazată pe cunoaștere, educarea și instruirea angajaților reprezintă o investiție în vederea obținerii unei performanțe îmbunătățite pe termen scurt, precum și a succesului pe termen lung al organizației.
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