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In dit zelfstudiepakket zit het officiële cursusmateriaal, een labomgeving, MeasureUp-oefenexamen en een Microsoft-examenvoucher. Je hebt 180 dagen toegang tot de labomgeving.
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In dit zelfstudiepakket zit het officiële cursusmateriaal, een labomgeving, MeasureUp-oefenexamen en een Microsoft-examenvoucher. Je hebt 180 dagen toegang tot de labomgeving. Bij deze labs kun je de modules slechts één keer uitvoeren. Begin pas aan een module als je voldoende tijd hebt om de labopdracht af te maken.
Dit zelfstudiepakket is identiek aan het zelfstudiepakket Data Engineering on Microsoft Azure (DP-203).
Data wordt steeds belangrijker. We hebben meer gegevens en we hebben meer soorten gegevens en we hebben meer verschillende toepassingen voor gegevens dan enkele jaren terug. Een andere trend is dat we steeds meer in de cloud gaan doen. De cloud heeft dan ook veel services te bieden om gegevens op te slaan en te verwerken. Zo ook Azure, de cloud van Microsoft. Deze cursus gaat over de Azure Data services die wij kunnen gebruiken om data driven oplossingen te bouwen.
Deze cursus zet de belangrijkste Azure Data Services op een rij. Aan de operationele kant leer over Azure SQL Databases en over Azure Cosmos DB. Aan de Business Intelligence kant leer je over Azure Synapse en Databricks. In beiden kan Azure Storage een rol spelen. En met Azure Stream Analytics komt ook real-time verwerking van gegevens aan bod.
Data engineers. Mensen die advies moeten geven over welke data services hoe in te zetten. Mensen die de gemaakte keuzes ook daadwerkelijk tot werkelijkheid maken.
Verkrijgen van praktische toepasbare kennis en vaardigheden en voorbereiding op het afsluitende officiële Microsoft-examen DP-203 Implementing an Azure Data Solution.
Je leert over Azure Srorage, Azure SQL Database, Azure Synapse, Databricks, Azure Cosmos DB, Azure Stream Analytics alsmede over Azure security en monitoring.
This module provides an overview of the Azure compute and storage technology options that are available to data engineers building analytical workloads. This module teaches ways to structure the data lake, and to optimize the files for exploration, streaming, and batch workloads. The student will learn how to organize the data lake into levels of data refinement as they transform files through batch and stream processing. Then they will learn how to create indexes on their datasets, such as CSV, JSON, and Parquet files, and use them for potential query and workload acceleration.
Introduction to Azure Synapse Analytics
Describe Azure Databricks
Introduction to Azure Data Lake storage
Describe Delta Lake architecture
Work with data streams by using Azure Stream Analytics
After completing this module, students will be able to:
Describe Azure Synapse Analytics
Describe Azure Databricks
Describe Azure Data Lake storage
Describe Delta Lake architecture
Describe Azure Stream Analytics
In this module, students will learn how to work with files stored in the data lake and external file sources, through T-SQL statements executed by a serverless SQL pool in Azure Synapse Analytics. Students will query Parquet files stored in a data lake, as well as CSV files stored in an external data store. Next, they will create Azure Active Directory security groups and enforce access to files in the data lake through Role-Based Access Control (RBAC) and Access Control Lists (ACLs).
Explore Azure Synapse serverless SQL pools capabilities
Query data in the lake using Azure Synapse serverless SQL pools
Create metadata objects in Azure Synapse serverless SQL pools
Secure data and manage users in Azure Synapse serverless SQL pools
After completing this module, students will be able to:
Understand Azure Synapse serverless SQL pools capabilities
Query data in the lake using Azure Synapse serverless SQL pools
Create metadata objects in Azure Synapse serverless SQL pools
Secure data and manage users in Azure Synapse serverless SQL pools
This module teaches how to use various Apache Spark DataFrame methods to explore and transform data in Azure Databricks. The student will learn how to perform standard DataFrame methods to explore and transform data. They will also learn how to perform more advanced tasks, such as removing duplicate data, manipulate date/time values, rename columns, and aggregate data.
Describe Azure Databricks
Read and write data in Azure Databricks
Work with DataFrames in Azure Databricks
Work with DataFrames advanced methods in Azure Databricks
After completing this module, students will be able to:
Describe Azure Databricks
Read and write data in Azure Databricks
Work with DataFrames in Azure Databricks
Work with DataFrames advanced methods in Azure Databricks
This module teaches how to explore data stored in a data lake, transform the data, and load data into a relational data store. The student will explore Parquet and JSON files and use techniques to query and transform JSON files with hierarchical structures. Then the student will use Apache Spark to load data into the data warehouse and join Parquet data in the data lake with data in the dedicated SQL pool.
Understand big data engineering with Apache Spark in Azure Synapse Analytics
Ingest data with Apache Spark notebooks in Azure Synapse Analytics
Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
Integrate SQL and Apache Spark pools in Azure Synapse Analytics
After completing this module, students will be able to:
Describe big data engineering with Apache Spark in Azure Synapse Analytics
Ingest data with Apache Spark notebooks in Azure Synapse Analytics
Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
Integrate SQL and Apache Spark pools in Azure Synapse Analytics
This module teaches students how to ingest data into the data warehouse through T-SQL scripts and Synapse Analytics integration pipelines. The student will learn how to load data into Synapse dedicated SQL pools with PolyBase and COPY using T-SQL. The student will also learn how to use workload management along with a Copy activity in a Azure Synapse pipeline for petabyte-scale data ingestion.
Use data loading best practices in Azure Synapse Analytics
Petabyte-scale ingestion with Azure Data Factory
After completing this module, students will be able to:
Use data loading best practices in Azure Synapse Analytics
Petabyte-scale ingestion with Azure Data Factory
This module teaches students how to build data integration pipelines to ingest from multiple data sources, transform data using mapping data flowss, and perform data movement into one or more data sinks.
Data integration with Azure Data Factory or Azure Synapse Pipelines
Code-free transformation at scale with Azure Data Factory or Azure Synapse Pipelines
After completing this module, students will be able to:
Perform data integration with Azure Data Factory
Perform code-free transformation at scale with Azure Data Factory
In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines.
After completing this module, students will be able to:
In this module, students will learn how to secure a Synapse Analytics workspace and its supporting infrastructure. The student will observe the SQL Active Directory Admin, manage IP firewall rules, manage secrets with Azure Key Vault and access those secrets through a Key Vault linked service and pipeline activities. The student will understand how to implement column-level security, row-level security, and dynamic data masking when using dedicated SQL pools.
Secure a data warehouse in Azure Synapse Analytics
Configure and manage secrets in Azure Key Vault
Implement compliance controls for sensitive data
After completing this module, students will be able to:
Secure a data warehouse in Azure Synapse Analytics
Configure and manage secrets in Azure Key Vault
Implement compliance controls for sensitive data
In this module, students will learn how Azure Synapse Link enables seamless connectivity of an Azure Cosmos DB account to a Synapse workspace. The student will understand how to enable and configure Synapse link, then how to query the Azure Cosmos DB analytical store using Apache Spark and SQL serverless.
Design hybrid transactional and analytical processing using Azure Synapse Analytics
Configure Azure Synapse Link with Azure Cosmos DB
Query Azure Cosmos DB with Apache Spark pools
Query Azure Cosmos DB with serverless SQL pools
After completing this module, students will be able to:
Design hybrid transactional and analytical processing using Azure Synapse Analytics
Configure Azure Synapse Link with Azure Cosmos DB
Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics
Query Azure Cosmos DB with SQL serverless for Azure Synapse Analytics
In this module, students will learn how to process streaming data with Azure Stream Analytics. The student will ingest vehicle telemetry data into Event Hubs, then process that data in real time, using various windowing functions in Azure Stream Analytics. They will output the data to Azure Synapse Analytics. Finally, the student will learn how to scale the Stream Analytics job to increase throughput.
Enable reliable messaging for Big Data applications using Azure Event Hubs
Work with data streams by using Azure Stream Analytics
Ingest data streams with Azure Stream Analytics
After completing this module, students will be able to:
Enable reliable messaging for Big Data applications using Azure Event Hubs
Work with data streams by using Azure Stream Analytics
Ingest data streams with Azure Stream Analytics
In this module, students will learn how to ingest and process streaming data at scale with Event Hubs and Spark Structured Streaming in Azure Databricks. The student will learn the key features and uses of Structured Streaming. The student will implement sliding windows to aggregate over chunks of data and apply watermarking to remove stale data. Finally, the student will connect to Event Hubs to read and write streams.
After completing this module, students will be able to:
Hieronder is een overzicht te vinden van trainingsmogelijkheden voor de Azure Data Engineering Zelfstudiepakket training, met zowel klassikale als virtuele trainingen. Selecteer de best passende optie en start jouw reis naar succes.
Al 25 jaar dé opleider op het gebied van IT in Nederland
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