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During this course you will learn how to design and implement 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.
Your course package is designed to provide maximum learning and convenience. This is included in the price of your course:
Your expert instructor will get you ready for the following exams and certification, which are included in your course package and covered by the Certification guarantee.
In addition to their professional experience, students who take this training should have technical knowledge equivalent to the Microsoft Azure Fundamentals course.
Using our engaging learning methodology including a variety of tools, we’ll cover the entire curriculum.
Course DP-200T01-A: Implementing an Azure Data Solution
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.
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 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.
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 learn 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, 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.
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 your 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 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.
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
- Creating and Querying an Azure SQL Data Warehouse
- Using 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.
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
- 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.
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 be able to:
- Azure Data Factory and Databricks
- Azure Data Factory Components
- 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 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.
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 be able to:
- 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.
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
Course DP-201T01-A: Designing an Azure Data Solution
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.
Lessons
- 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
Lab : Case Study
- Design with security in mind
- Consider performance and scalability
- Design for availability and recoverability
- Design for efficiency and operations
After completing this module, students will be able to:
- Design with Security in mind
- Consider performance and scalability
- Design for availability and recoverability
- Design for efficiency and operations
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.
Lessons
- 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
Lab : Architect an Enterprise-grade Conversational Bot in Azure
- Designing an Enterprise BI solution in Azure
- Automate an Enterprise BI solution in Azure
- Automate an Enterprise BI solution in Azure
After completing this module, students will be able to:
- 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
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.
Lessons
- 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
Lab : Azure Real-Time Reference Architectures
- Architect a stream processing pipeline with Azure Stream Analytics
- Design a stream processing pipeline with Azure Databricks
- Create an Azure IoT reference architecture
After completing this module, students will be able to:
- 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
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.
Lessons
- Defense in Depth Security Approach
- Identity Management
- Infrastructure Protection
- Encryption Usage
- Network Level Protection
- Application Security
Lab : Data Platform Security Design Considerations
- Defense in Depth Security Approach
- Identity Protection
After completing this module, students will be able to:
- 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.
Lessons
- 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
Lab : Designing for Resiliency and Scale
- Adjust Workload Capacity by Scaling
- Design for Optimized Storage and Database Performance
- Design a Highly Available Solution
- Incorporate Disaster Recovery into Architectures
After completing this module, students will be able to:
- 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.
Lessons
- Maximizing the Efficiency of your Cloud Environment
- Use Monitoring and Analytics to Gain Operational Insights
- Use Automation to Reduce Effort and Error
Lab : Design for Efficiency and Operations
- Maximize the Efficiency of your Cloud Environment
- Use Monitoring and Analytics to Gain Operational Insights
- Use Automation to Reduce Effort and Error
After completing this module, students will be able to:
- Maximize the Efficiency of your Cloud Environment
- Use Monitoring and Analytics to Gain Operational Insights
- Use Automation to Reduce Effort and Error
The Virtual Classroom is an online room, where you will join your instructor and fellow classmates in real time. Everything happens live and you can interact freely, discuss, ask questions, and watch your instructor present on a whiteboard, discuss the courseware and slides, work with labs, and review.
Yes, you can sit exams from all the major Vendors like Microsoft, Cisco etc from the comfort of your home or office.
With Readynez you do any course form the comfort of your home or office. Readynez provides support and best practices for your at-home classroom and you can enjoy learning with minimal impact on your day-to-day life. Plus you'll save the cost and the environmental burden of travelling.
Well, learning is limitless, when you are motivated, but you need the right path to achieve what you want. Readynez consultants have many years of experience customizing learner paths and we can design one for you too. We are always available with help and guidance, and you can reach us on the chat or write us at info@readynez.com.