Booking options
£2,380
+ VAT£2,380
+ VATDelivered Online
All levels
Duration
4 Days
24 CPD hours
This course is intended for
The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.
In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.
Prerequisites
Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.
AZ-900T00 Microsoft Azure Fundamentals
DP-900T00 Microsoft Azure Data Fundamentals
What is data engineering
Important data engineering concepts
Data engineering in Microsoft Azure
Understand Azure Data Lake Storage Gen2
Enable Azure Data Lake Storage Gen2 in Azure Storage
Compare Azure Data Lake Store to Azure Blob storage
Understand the stages for processing big data
Use Azure Data Lake Storage Gen2 in data analytics workloads
What is Azure Synapse Analytics
How Azure Synapse Analytics works
When to use Azure Synapse Analytics
Understand Azure Synapse serverless SQL pool capabilities and use cases
Query files using a serverless SQL pool
Create external database objects
Transform data files with the CREATE EXTERNAL TABLE AS SELECT statement
Encapsulate data transformations in a stored procedure
Include a data transformation stored procedure in a pipeline
Understand lake database concepts
Explore database templates
Create a lake database
Use a lake database
Get to know Apache Spark
Use Spark in Azure Synapse Analytics
Analyze data with Spark
Visualize data with Spark
Modify and save dataframes
Partition data files
Transform data with SQL
Understand Delta Lake
Create Delta Lake tables
Create catalog tables
Use Delta Lake with streaming data
Use Delta Lake in a SQL pool
Design a data warehouse schema
Create data warehouse tables
Load data warehouse tables
Query a data warehouse
Load staging tables
Load dimension tables
Load time dimension tables
Load slowly changing dimensions
Load fact tables
Perform post load optimization
Understand pipelines in Azure Synapse Analytics
Create a pipeline in Azure Synapse Studio
Define data flows
Run a pipeline
Understand Synapse Notebooks and Pipelines
Use a Synapse notebook activity in a pipeline
Use parameters in a notebook
Understand hybrid transactional and analytical processing patterns
Describe Azure Synapse Link
Enable Cosmos DB account to use Azure Synapse Link
Create an analytical store enabled container
Create a linked service for Cosmos DB
Query Cosmos DB data with Spark
Query Cosmos DB with Synapse SQL
What is Azure Synapse Link for SQL?
Configure Azure Synapse Link for Azure SQL Database
Configure Azure Synapse Link for SQL Server 2022
Understand data streams
Understand event processing
Understand window functions
Stream ingestion scenarios
Configure inputs and outputs
Define a query to select, filter, and aggregate data
Run a job to ingest data
Use a Power BI output in Azure Stream Analytics
Create a query for real-time visualization
Create real-time data visualizations in Power BI
What is Microsoft Purview?
How Microsoft Purview works
When to use Microsoft Purview
Catalog Azure Synapse Analytics data assets in Microsoft Purview
Connect Microsoft Purview to an Azure Synapse Analytics workspace
Search a Purview catalog in Synapse Studio
Track data lineage in pipelines
Get started with Azure Databricks
Identify Azure Databricks workloads
Understand key concepts
Get to know Spark
Create a Spark cluster
Use Spark in notebooks
Use Spark to work with data files
Visualize data
Understand Azure Databricks notebooks and pipelines
Create a linked service for Azure Databricks
Use a Notebook activity in a pipeline
Use parameters in a notebook
Additional course details:
Nexus Humans DP-203T00 Data Engineering on Microsoft Azure training program is a workshop that presents an invigorating mix of sessions, lessons, and masterclasses meticulously crafted to propel your learning expedition forward.
This immersive bootcamp-style experience boasts interactive lectures, hands-on labs, and collaborative hackathons, all strategically designed to fortify fundamental concepts.
Guided by seasoned coaches, each session offers priceless insights and practical skills crucial for honing your expertise. Whether you're stepping into the realm of professional skills or a seasoned professional, this comprehensive course ensures you're equipped with the knowledge and prowess necessary for success.
While we feel this is the best course for the DP-203T00 Data Engineering on Microsoft Azure course and one of our Top 10 we encourage you to read the course outline to make sure it is the right content for you.
Additionally, private sessions, closed classes or dedicated events are available both live online and at our training centres in Dublin and London, as well as at your offices anywhere in the UK, Ireland or across EMEA.
Nexus Human, established over 20 years ago, stands as a pillar of excellence in the realm of IT and Business Skills Training and education in Ireland and the UK....