Microsoft Certified: Azure Data Engineer Associate: DP-203: Data Engineering on Microsoft Azure

  • 20 Courses | 26h 42m 3s
  • Includes Lab
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Explore how to build and maintain secure and compliant data processing pipelines by using different tools and techniques as you prepare for the DP-203: Data Engineering on Microsoft Azure certification exam.

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Data Engineering on Microsoft Azure: Storage Accounts

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COURSES INCLUDED

Data Engineering on Microsoft Azure: Storage Accounts
Microsoft Azure Blob storage is a container system for storing a variety of file types. In this course, you'll learn about the capabilities of blob storage and how to architect a deployment for optimal performance and scalability. Then, you'll explore the options for redundancy and how to recover from disasters. You'll discover where Azure Data Lake Storage Gen2, a feature set within blob storage, can be utilized for big data operations. You'll also learn how to plan for a data lake deployment, examine best practices, and explore how to deploy a Data Lake Gen2 account on Azure. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 16m has Assessment available Badge
Data Engineering on Microsoft Azure: Designing Data Storage Structures
Planning the structure for data storage is integral to performance in big data operations. In this course, you'll learn about key considerations for data lakes and how to determine which file type and file format are the most appropriate for your use case. Then, you'll explore how to define how to design table storage for efficient querying and how data pruning can remove unnecessary data to accelerate transactions. You'll examine folder structures and data lake zones for organizing data effectively. Finally, you'll learn how to define storage tiers and how to manage the life cycle of data. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 12m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Partitioning
Partitioning data is key to ensuring efficient processing. In this course, you'll explore what data partitioning is and the strategies for implementation. You'll learn about transactional and analytical workloads and how to determine the best strategy for your files and table storage. Then, you'll examine design patterns for efficiency and performance. You'll learn about partitioning dedicated SQL pools in Azure Synapse Analytics and partitioning data lakes. Finally, you'll learn how data sharding across multiple data stores can be used for improving transaction performance. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 7m has Assessment available Badge
Data Engineering on Microsoft Azure: Designing the Serving Layer
The serving layer is where data is stored for consumption by processing services. In this course, you'll explore dimensional data modeling and hierarchies. You'll learn how to define slowly changing dimensions and temporal design within databases. Then, you'll learn about the differences between the star and snowflake schemas as well as how to design a star schema. Next, you'll examine incremental data loading for stream processing and the options for analytical data stores. Finally, you'll learn about options for creating metastores for use by Azure Databricks and Azure Synapse Analytics. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 16m has Assessment available Badge
Data Engineering on Microsoft Azure: Physical Data Storage Structures
An effective storage structure is critical to big data implementation success. In this course, you'll explore data compression in databases and file storage. Then, you'll discover how partitioning and sharding are implemented in the database. Next, you'll explore designing tables in an Azure Synapse Analytics dedicated SQL pool, and implement geo-replication for redundancy in both databases and Azure Blob storage. You'll also discover implementing distribution schemes in Azure Synapse Analytics. Finally, you'll discover data archiving and long-term retention policies for Azure Blob storage and Azure SQL Databases. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 9m has Assessment available Badge
Data Engineering on Microsoft Azure: Logical Data Structures
Logical data structures, also called entity-relationship models, are models used to define a high-level model of data and the relationships contained within. In this course, you'll learn about the stages of data lake maturity. You'll explore temporal database tables and how to manage them. You'll also learn how to define slowly changing dimensions and how to implement them. You'll then move on to explore logical file and folder structures for data ingestion. You'll discover how PolyBase can be used to connect to external tables. Finally, you'll explore the best practices for accelerating queries. This course is one in a collection that prepares learners for the Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 36m has Assessment available Badge
Data Engineering on Microsoft Azure: The Serving Layer
Implementing an effective serving layer requires consideration for the design, methods, and tools. In this course, you'll learn how traditional relational models can be replaced by the star schema and how to design a star schema. Then, you'll explore the purpose and structure of Parquet files used by Azure Databricks. You'll learn how to design and query a dimensional hierarchy. You'll move on to examine Azure Synapse Analytics, including deploying dedicated SQL pools and Apache Spark clusters. Finally you'll learn how to create shared metadata tables between Spark clusters. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 8m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Policies & Standards
Data policies and standards help to ensure a repeatable security standard is maintained. In this course, you'll learn about data encryption scenarios and best practices. You'll explore how Azure Transparent Database Encryption and Always Encrypted can be used to ensure data at rest is protected. Next, you'll examine how data classification and data masking can protect data being viewed. You'll learn to configure data retention and purging to ensure data is retained or removed. You'll also explore the various means of controlling access to Azure Data Lake Storage Gen2. Finally, you'll learn how to plan a data auditing strategy and how to limit access to data at the row level in a database. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 7m has Assessment available Badge
Data Engineering on Microsoft Azure: Securing Data Access
Securing access to data is a fundamental part of any security strategy. In this course, you'll explore how Azure Key Vault can be used to store and manage keys and secrets for accessing data. You'll discover how to connect to Azure resources through private and service endpoints and managed virtual networks and how to use Azure managed identities for connections between Azure resources. Next, you'll learn how to utilize access control lists and Azure role-based access control to provide only the necessary permissions to users to access your data. You'll also learn how token-based authentication works in Azure Databricks. Finally, you'll examine how to audit an Azure SQL Database to monitor for unauthorized access. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
12 videos | 1h 11m has Assessment available Badge
Data Engineering on Microsoft Azure: Securing Data
The final line of defense for protecting against a data breach is securing the data itself. With today's cloud environments, data is often in transit, duplicated, and stored in various data centers around the world, making effective data protection a challenge. In this course, you'll explore the various methods available for encrypting data stored in SQL databases. You'll examine how to use DataFrames in Databricks, as well as how to implement Advanced Threat Protection and dynamic data masking in Azure databases. Finally, you'll learn how immutable blobs can be used to manage sensitive information. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 25m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Lake Storage
Azure Data Lake Storage Gen2 provides features to work with big data analytics using Azure Blob Storage. Azure Blob Storage systems provide performance, management, and security functionality. In this course, you'll learn about the features of the Azure Data Lake Storage Gen2 and when to use this storage type. You'll explore features and methods for securing data for the Azure Data Lake Storage Gen2 service and data at rest. You'll examine methods for processing big data using the Azure Data Lake Storage Gen2 service and monitoring Azure Blob Storage. You'll learn how to manage directories, files, and Access Control Lists in Azure Data Lake Storage Gen2 using the .NET framework, as well as how to perform extract, transform, and load operations using Azure Databricks from Azure Data Lake Storage Gen2. Finally, you'll learn how to access Azure Data Lake Storage Gen2 data using Azure Databricks and Spark. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 51m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Flow Transformations
One of the key components of the Azure Cloud platform is the ability to store and process large amounts of data. Azure Data Flow Transformations can be used to ingest and transform data. In this course, you'll learn about the types of Azure Data Flow transformations that are available. You'll explore how to transform, split, and flatten data, as well as handle duplicate data, using Azure Data Mapping Data Flows. Next, you'll examine the types of expression functions available in Azure Data Flow and how to perform error handling for data rows that would truncate data. Finally, you'll learn how to transform and use derived columns to normalize data values, and how to ingest and transform data using Azure Spark and Scala. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 27m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Factory
Once you have data in storage, you'll need to have some mechanism for transforming the data into a usable format. Azure Data Factory is a data integration service that is used to create automated data pipelines that can be used to copy and transform data. In this course, you'll learn about the Azure Data Factory and the Integration Runtime. You'll explore the features of the Azure Data Factory such as linked services and datasets, pipelines and activities, and triggers. Finally, you'll learn how to create an Azure Data Factory using the Azure portal, create Azure Data Factory linked services and datasets, create Azure Data Factory pipelines and activities, and trigger the pipeline manually or using a schedule. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
13 videos | 2h 28m has Assessment available Badge
Data Engineering on Microsoft Azure: Databricks
When working with big data, there needs to be a mechanism to process and transform this data quickly and efficiently. Azure Databricks is a service that provides the latest version of Apache Spark, which provides functionality for machine learning and data warehousing. In this course, you'll learn about the features of Azure Databricks such as clusters, notebooks, and jobs. Next, you'll learn about autoscaling local storage when configuring clusters. Next, you'll explore how to create, manage, and configure Azure Databricks clusters, as well as how to create, open, use, and delete notebooks. Finally, you'll learn how to create, open, use, and delete jobs. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 2m has Assessment available Badge
Data Engineering on Microsoft Azure: Databrick Processing
When working with big data there needs to be a mechanism to process and transform this data quickly and efficiently. Azure Databricks is a service that provides the latest version of Apache Spark that provides functionality processing data from Azure Storage. In this course, you will learn about the types of processing that can be performed with Azure Databricks such as stream, batch, image and parallel processing. Next, you'll learn how to create an Azure Databricks workspace using an Apache Spark cluster, run jobs in the Azure Databricks Workspace jobs using a service principal and query data in SQL server using an Azure Databricks notebook. Next, you'll learn how to retrieve data from an Azure Blob Storage using Azure Databricks and the Azure Key Vault, implement a Cosmos DB service endpoint for Azure Databricks, and extract, transform, and load data using Azure Databricks. Finally, you'll learn how to stream data into Azure Databricks by using Event Hubs and perform sentiment analysis for steam data by making use of Azure Databricks. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 1h 53m has Assessment available Badge
Data Engineering on Microsoft Azure: Stream Analytics
Azure Stream Analytics is a complex, serverless, and highly scalable processing engine that can be used to perform real-time analytics on multiple data streams. Alerts can be configured to forecast trends, trigger workflows, and detect irregularities. In this course, you'll learn to use Azure Stream Analytics to process streaming data. You'll examine how to implement security, create user-defined functions, and optimize jobs for Azure Stream Analytics, as well as explore the available inputs and outputs. Finally, you'll learn how to create an Azure Stream Analytics job, create an Azure Stream Analytics dedicated cluster, run Azure Functions from Azure Stream Analytics jobs, and monitor Azure Stream Analytics jobs. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
10 videos | 1h 12m has Assessment available Badge
Data Engineering on Microsoft Azure: Synapse Analytics
Azure Synapse Analytics is an analytics service that provides functionality for data integration, enterprise data warehousing, and big data analytics. Services provided include ingesting, exploring, preparing, managing, and serving data for BI and machine learning needs. In this course, you'll learn about the Azure Synapse Analytics platform and how it is used for data warehousing and big data analytics. Next, you'll learn how to create a Synapse Workspace, a dedicated SQL pool, and a serverless Apache Spark pool. You'll move on to explore how to analyze data using a dedicated SQL pool, Apache Spark for Azure Synapse, Serverless SQL Pools, and a Spark database, as well as how to analyze data that is in a storage account. You'll learn how to integrate pipelines using Synapse Studio, visualize data using a Power BI workspace, and monitor a Synapse Workspace. Finally, you'll learn about the Synapse Knowledge Center and the features of Azure Synapse Analytics and PolyBase. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
8 videos | 45m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Storage Monitoring
Being able to monitor data storage systems to ensure they are operational and working correctly is a crucial part of running your business. Azure provides the Azure Monitor service and the Azure Log Analytics service to perform this function. In this course, you'll learn about the features of Azure Log Analytics, as well as the Azure Monitor service and how it can be used to monitor storage data and monitor Azure Blob storage. Next, you'll explore how to access diagnostic logs to monitor Data Lake Storage Gen2, monitor the Azure Synapse Analytics jobs and the adaptive cache, and monitor Azure Cosmos DB using the portal and resource logs. Finally, you'll examine how to configure, manage, and view metric alerts using the Azure Monitor and activity log alerts using the Azure Monitor. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
12 videos | 58m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Process Monitoring
Being able to monitor data processes to ensure they are operational and working correctly is a crucial part of running your business. Azure provides the Azure Monitor service and the Azure Log Analytics service to perform this function. In this course, you'll learn about the features of the Azure Monitor tools and the concepts of continuous monitoring and visualization. Next, you'll examine how to create metric charts using the Azure Monitor, as well as how to collect and analyze Azure resource log data and perform queries against the Azure Monitor logs. You'll explore how to create and share dashboards that display data from Log Analytics, create Azure Monitor alerts, and use the Azure Data Factory Analytics solution to monitor pipelines. You'll learn how to send the Azure Databricks logs to the Azure Monitor and use the dashboard to analyze the Azure Databricks metrics. Finally, you'll learn how to enable monitoring for Azure Stream Analytics and configure alerts, and also query Azure Log Analytics and filter, sort, and group query results. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
15 videos | 1h 31m has Assessment available Badge
Data Engineering on Microsoft Azure: Data Solution Optimization
Ensuring that data storage and processing systems are operating efficiently will allow your organization to save both time and money. There are several tips and tricks that can be used to optimize both Azure Data Storage service and processes. In this course, you'll learn about cloud optimization, as well as some best practices for optimizing data using data partitions, Azure Data Lake Storage tuning, Azure Synapse Analytics tuning, and Azure Databricks auto-optimizing. Next, you'll learn about strategies for partitioning data using Azure-based storage solutions. You'll learn about the stages of the Azure Blob lifecycle management and how to optimize Azure Data Lake Storage Gen2, Azure Stream Analytics, and Azure Synapse Analytics. Finally, you'll explore how to optimize Azure Data Storage services such Azure Cosmos DB using indexing and partitioning, as well as Azure Blob Storage and Azure Databricks. This course is one in a collection that prepares learners for the Microsoft Data Engineering on Microsoft Azure (DP-203) exam.
11 videos | 58m has Assessment available Badge
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