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.
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.
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.
Pe lângă experiența profesională, studenții care parcurg acest curs ar trebui să aibă cunoștințe tehnice echivalente următorului curs: Azure Fundamentals.
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
Acest curs îi pregătește pe studenți pentru susținerea examenului Microsoft DP-200.
Detalii curs
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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