Wil jij leren hoe jij datagestuurde oplossingen kunt ontwikkelen met behulp van Microsoft Azure? De Azure Data Engineering E-Learning is identiek aan de DP-203 E-Learning en biedt jou een diepgaande inleiding op Azure Data Services, inclusief Azure SQL Databases, Cosmos DB, Synapse, Databricks en Stream Analytics. Verder bestaat de Azure Data Engineering E-Learning uit het cursusmateriaal, een labomgeving (die 180 dagen toegankelijk is), een MeasureUp oefenexamen en een DP-203 examenvoucher.
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Pakket aanschaffenThe Azure Data Engineering E-Learning is entirely in English. As a Dutch IT training provider, we offer the information on this page in Dutch. At the bottom of the page, you will find a brief summary in English. The topics within the Azure Data Engineering E-Learning package itself are described in English.
Data speelt een steeds grotere rol in organisaties en met de overstap naar de cloud, groeit de behoefte aan efficiënte opslag- en verwerkingsoplossingen. De Azure Data Engineering E-Learning biedt jou een diepgaande inleiding op de datadiensten van Microsoft Azure. Tevens zul je leren hoe jij datagestuurde oplossingen kunt ontwikkelen met behulp van de krachtige cloudtechnologieën binnen Microsoft Azure.
Door de Azure Data Engineering E-Learning door te nemen, zul je inzicht krijgen in Azure Data Services. Je leert bijvoorbeeld hoe Azure SQL Databases en Azure Cosmos DB worden ingezet voor operationele dataopslag en hoe Azure Synapse en Databricks bijdragen aan Business Intelligence-oplossingen. Daarnaast zul je met de Azure Data Engineering E-Learning ontdekken hoe Azure Storage en Azure Stream Analytics een rol spelen in zowel batch- als real-time (tijdsgetrouwe) gegevensverwerking.
De Azure Data Engineering E-Learning is identiek aan de DP-203 E-Learning en bestaat uit het cursusmateriaal, een labomgeving (die 180 dagen toegankelijk is), een MeasureUp oefenexamen en een DP-203 examenvoucher. 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.
De Azure Data Engineering E-Learning is ontworpen voor professionals die zich willen verdiepen in data-engineering en gebruik willen leren maken van Azure Data Services.
Dit betreft met name de volgenden mensen:
Met de Azure Data Engineering E-Learning krijg je zowel theoretische kennis als praktische vaardigheden om Azure Data Services effectief in te zetten. Door te oefenen met behulp van de labopdrachten en het MeasureUp oefenexamen, zul jij je optimaal voorbereiden op het DP-203 examen en jouw expertise in data-engineering versterken. Verder biedt de Azure Data Engineering E-Learning jou een complete leerervaring waarmee je een stevige basis legt in Azure Data Services en data-engineering.
Hier is een overzicht van de inhoud van de Azure Data Engineering E-Learning:
Voordat je begint met de Azure Data Engineering E-Learning, is het van belang dat jij beschikt over de volgende kennis en vaardigheden:
Module 1: Explore compute and storage options for data engineering workloads
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.
Lessons:
Lab: Explore compute and storage options for data engineering workloads
After completing this module, students will be able to:
Module 2: Run interactive queries using Azure Synapse Analytics serverless SQL pools
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).
Lessons:
Lab: Run interactive queries using serverless SQL pools
After completing this module, students will be able to:
Module 3: Data exploration and transformation in Azure Databricks
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.
Lessons:
Lab: Data Exploration and Transformation in Azure Databricks
After completing this module, students will be able to:
Module 4: Explore, transform, and load data into the Data Warehouse using Apache Spark
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.
Lessons:
Lab: Explore, transform, and load data into the Data Warehouse using Apache Spark
After completing this module, students will be able to:
Module 5: Ingest and load data into the data warehouse
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.
Lessons:
Lab: Ingest and load Data into the Data Warehouse
After completing this module, students will be able to:
Module 6: Transform data with Azure Data Factory or Azure Synapse Pipelines
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.
Lessons:
Lab: Transform Data with Azure Data Factory or Azure Synapse Pipelines
After completing this module, students will be able to:
Module 7: Orchestrate data movement and transformation in Azure Synapse Pipelines
In this module, you will learn how to create linked services, and orchestrate data movement and transformation using notebooks in Azure Synapse Pipelines.
Lessons:
Lab: Orchestrate data movement and transformation in Azure Synapse Pipelines
After completing this module, students will be able to:
Module 8: End-to-end security with Azure Synapse Analytics
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.
Lessons:
Lab: End-to-end security with Azure Synapse Analytics
After completing this module, students will be able to:
Module 9: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
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.
Lessons:
Lab: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
After completing this module, students will be able to:
Module 10: Real-time Stream Processing with Stream 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.
Lessons:
Lab: Real-time Stream Processing with Stream Analytics
After completing this module, students will be able to:
Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks
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.
Lessons:
Lab: Create a Stream Processing Solution with Event Hubs and Azure Databricks
After completing this module, students will be able to:
The Azure Data Engineering E-Learning offers a comprehensive introduction to Microsoft Azure Data Services, including SQL Databases, Cosmos DB, Synapse, Databricks, and Stream Analytics. You will learn to develop data-driven solutions using Azure’s powerful cloud technologies, focusing on both batch and real-time data processing. The Azure Data Engineering E-Learning is identical to the DP-203 E-Learning, it includes the course materials, labs (accessible for 180 days), a MeasureUp practice exam, and a DP-203 exam voucher, preparing you for the DP-203 exam and practical applications in data engineering.
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.
In het Azure Data Engineering Zelfstudiepakket zit het officiële cursusmateriaal, een labomgeving, MeasureUp-oefenexamen en een Microsoft-examenvoucher. Je hebt 180 dagen toegang tot de labomgeving.
Het Azure Data Engineering Zelfstudiepakket is ideaal voor data engineers, analisten, en ICT-professionals die willen leren hoe ze data-oplossingen kunnen implementeren in Microsoft Azure.
Onderwerpen in het Azure Data Engineering Zelfstudiepakket zijn onder andere Azure Synapse Analytics, Azure Databricks, Data Lake storage, en real-time data verwerking met Stream Analytics.
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