Microsoft Azure Data Engineer (DP-200)

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Description

Microsoft Azure Synapse Analytics is a new environment that merges all the Azure data resources into one shared space. In this course, Implementing a Cloud Data Warehouse in Microsoft Azure Synapse Analytics, you'll focus on building an SQL data warehouse in Synapse. First, you'll learn what Azure Synapse Analytics does. Next, you'll discover how to deploy a data warehouse. Finally, you'll explore how to load data into your warehouse and work with it, saving money in the process. By the end of this course, you’ll have a working Synapse Analytics SQL data warehouse, loaded with data, that will let you work with all the new features.

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Discover the main Microsoft Azure managed NoSQL offerings. In this course, Implementing NoSQL Databases in Microsoft Azure, you will gain the ability to use Cosmos DB, Azure Table Storage and Azure Data Lake Gen2 for big data. First, you will learn about the cheap and fast Azure Table Storage NoSQL database. Next, you will discover the power of Azure Cosmos DB multi-model APIs for new and migrated NoSQL workloads. Finally, you will explore how to provision an Azure Data Lake Storage Gen2 instance and upload unstructured data to it. When you are finished with this course, you will have the skills and knowledge of managed NoSQL database offerings needed to start using NoSQL databases in Microsoft Azure.

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Azure SQL Database is Microsoft's main relational database offering in the cloud. Getting the most out of this sophisticated service can be a challenge. In this course, Implementing a Relational Database in Microsoft Azure SQL Database, you will gain the ability to quickly provision and configure your relational database in the cloud. First, you will learn which deployment option best suites your project. Next, you will discover the automatic backup and data sync features. Finally, you will explore how to create database scheduled jobs to meet your data management and other needs. When you are finished with this course, you will have the skills and knowledge of Azure SQL Database needed to deploy and run your relational databases in the cloud.

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Understanding the capabilities related to hybrid use for Azure data services can be overwhelming. In this course, Implementing Hybrid Data Solutions in Microsoft Azure, you will learn foundational knowledge of Azure data services use in a hybrid solution. First, you will learn core hybrid data considerations. Next, you will discover how to utilize Azure data services in a hybrid solution. Finally, you will explore how to optimize your data solution. When you’re finished with this course, you will have the skills and knowledge of hybrid data solutions needed to include Azure data services as part of a complete solution.

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Every day, we have more and more data, and the problem is how do we get to where we can use the data for business needs. In this course, Implementing a Databricks Environment in Microsoft Azure, you will learn foundational knowledge and gain the ability to implement Azure Databricks for use by all your data consumers like business users and data scientists. First, you'll learn the basics of Azure Databricks and how to implement ts components. Next, you will discover how to work with Azure Databricks during ETL (Extract, Transform, Load) operations. Then, you'll move on to performing batch scoring with machine learning models. Finally, you will explore how to work with streaming data from HDInsight Kafka. When you’re finished with this course, you will have the skills and knowledge of Azure Databricks needed to implement data pipeline solutions for your data consumers. Software required: Microsoft Azure Subscription

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Long-running batch data processing can be difficult to manage locally - why not use Microsoft Azure? In this course, Building Batch Data Processing Solutions in Microsoft Azure, you’ll gain the ability to perform high-scale ETL and ELT operations entirely in the Azure public cloud. First, you’ll explore hosted Apache Spark processing with Azure Databricks. Next, you’ll discover how to transfer data in bulk with Azure Data Factory and Azure Data Explorer. Finally, you’ll learn how to handle stream data processing jobs with Azure Stream Analytics. When you’re finished with this course, you’ll have the skills and knowledge of batch data processing needed to earn your Azure Data Engineer certification and be productive with the Microsoft Azure Data Platform.

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Processing live data streams in real time can be challenging and expensive. In this course, Building Streaming Data Pipelines in Microsoft Azure, you will gain the ability to effectively use Azure Stream Analytics for your live data processing needs. First, you will learn to configure stream and reference inputs for the service. Next, you will discover how to process your data using the Stream Analytics Query Language. Finally, you will explore how to visualize Azure Stream Analytics output with Microsoft Power BI. When you are finished with this course, you will have the skills and knowledge of Azure Stream Analytics needed to turn your live stream data into meaningful, actionable information.

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Data-driven decision making is the path to business success. In this course, Integrating Data in Microsoft Azure, you will gain foundational knowledge to integrate data utilizing the power of Microsoft Azure.

First, you will learn how to migrate data from on-premise and Amazon Web Services to Azure. Next, you will discover how to easily construct ETL processes and create data integration pipelines using Azure Data Factory.

Finally, you will explore how to create a real-time pipeline, to ingest and process real-time events sent by IoT devices using Azure EventHubs, Azure Stream Analytics, and Power BI.

When you’re finished with this course, you will have the skills and knowledge needed to create data integration pipelines using some of the great tools that are part of the Azure ecosystem.

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Agile methodologies have radically changed application development. Databases now need to continually evolve along with our applications, especially with the focus on highly iterative, micro-service driven architectures. In this course, Deploying Microsoft Azure SQL Data Warehouse and Azure SQL Database, you will learn foundational knowledge to create and deploy databases as part of a CI/CD process. First, you'll learn to create new Azure SQL Databases, Azure Data Warehouses, and Azure Data Factory resources along with creating ARM templates for each resource. Next, you’ll learn how to set up build and release pipelines with Azure DevOps to automatically provision new resources using ARM templates and deploying data warehouse or SQL database using data-tier application packages (DACPAC). Finally, you'll explore how to migrate existing on-premises SQL Server Databases to Azure using Azure Migrate Service, or keeping your on-premises databases automatically synchronized with Azure SQL Databases using Azure Data Sync. When you’re finished with this course, you will have the skills and knowledge to use Azure DevOps to deploy both Azure SQL Data Warehouses and Azure SQL Databases as part of your Agile processes.

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Data engineers working with Azure Data Factory can take advantage of Continuous Integration and Continuous Delivery practices to deploy robust and well-tested data pipelines to production.

In this course, Deploying Data Pipelines in Microsoft Azure, you will learn foundational knowledge to apply CI/CD methodologies to your data pipeline creation process.

First, you will learn to create the right environments to fall into the pit of success when creating data pipelines in ADF.

Next, you will discover how to deploy data pipelines using ADF visual tools and ARM templates.

Finally, you will explore how to create a release pipeline in Azure DevOps to automate the deployment process between three distinct environments: development, staging, and production.

When you are finished with this course, you will have the skills and knowledge to apply CI/CD practices to your data pipeline creation process, effortlessly.

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Description

On first glance, SQL Server and containers seem complete opposites, but running SQL Server containers in Azure provides a number of business and technical benefits. In this course, Deploying SQL Server Containers in Microsoft Azure, you will gain the ability to design and deploy a container-based SQL Server deployment in Azure. First, you will learn core skills around containers and Kubernetes. Next, you will discover how to deploy SQL Server in a container. Finally, you will explore how to piece everything together by deploying SQL Server to container services hosted in Azure, while meeting key SQL Server requirements. When you’re finished with this course, you will have the skills and knowledge of deploying SQL Server containers in Azure needed to meet your business and technical goals.

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Understanding the right ways to gain monitoring insight to Azure Storage services and HDInsight can be challenging. In this course, Monitoring Microsoft Azure Data Storage, you will learn foundational knowledge of monitoring these services in Azure. First, you will learn core skills around Azure Monitor. Next, you will discover Azure Storage-specific aspects of monitoring. Finally, you will explore how to monitor HDInsight, including using the open source monitoring components. When you’re finished with this course, you will have the skills and knowledge of monitoring needed to achieve all the insight required for Azure Storage and HDInsight.

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Using database services in the cloud can initially present challenges as to the right way to monitor the deployments. In this course, Microsoft Azure Database Monitoring Playbook, you will gain the ability to implement and use monitoring to achieve the results required. First, you will learn key aspects of monitoring databases in Azure. Next, you will discover monitoring options for Azure SQL Database in the portal and beyond. Finally, you will explore how to monitor Azure Cosmos DB and use that monitoring to ensure proper data partitioning. When you’re finished with this course, you will have the skills and knowledge of monitoring Azure database offerings needed to ensure the smooth operation and use of Azure-based deployments.

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Organizations need to get business insights from multiple, disparate sources and it is important that the pipelines and processes that enable this insight are healthy. In this course, Monitoring Microsoft Azure Data Pipelines and Processing, you will learn foundational knowledge of the core structure of data pipeline services and how to monitor them. First, you will examine the foundation of data pipelines and processes. Next, you will discover how to monitor Azure Data Factory as a control flow solution. Finally, you will explore how to monitor the HDInsight and Databricks data flow solution. When you’re finished with this course, you will have the skills and knowledge of monitoring data pipelines and processes needed to ensure the health and accuracy of generated business insights.

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Proactive notification of issues is critical for data services. In this course, Microsoft Azure Alert Configuration Playbook, you will learn foundational knowledge of alerting technologies and options available in Azure. First, you will examine how to use the centralized alerting in Azure Monitor. Next, you will discover additional alerting capabilities when utilizing Log Analytics-based queries. Finally, you will explore how to put these skills to use for specific data services. When you’re finished with this course, you will have the skills and knowledge of alerting in Azure needed to ensure the right level of proactive communications related to incidents for data services in Azure.

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Getting the most out of cloud data service spend in terms of performance is critical for every organization. In this course, Optimizing Microsoft Azure Data Solutions, you will gain the ability to access and optimize a number of key data services in Azure. First, you will learn how to optimize Azure SQL Database and Azure SQL Data Warehouse. Next, you will discover the key optimization considerations related to Cosmos DB and the importance of partitioning data the right way. Finally, you will explore how to achieve maximum performance when using Azure Data Lake and a number of key analysis services. When you’re finished with this course, you will have the skills and knowledge of optimizing Azure data services needed to maximize your Azure data service deployments.