DP-203 | Data Engineering on Microsoft AzureSaturday 01 January
This course is designed to teach data engineering patterns and practices as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies. Delegates will learn core compute and storage technologies that are used to build an analytical solution. They will explore how to design analytical serving layers and focus on data engineering considerations for working with source files. They will also learn how to interactively explore data stored in files in a data lake, various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, how to ingest using Azure Data Factory or Azure Synapse pipelines and ways they can transform the data using the same technologies that is used to ingest data.
The outcomes of this course for delegates are:
- Exploring compute and storage options for workloads
- Designing and implementing the serving layer
- Understanding data engineering considerations
- Running interactive queries using serverless SQL pools
- ETL data into the Data Warehouse using Apache Spark
- Performing exploration and transformation in Azure Databricks
- Ingesting and loading data into the Data Warehouse
- Transforming with Data Factory or Azure Synapse Pipelines
- Integrating Data with Data Factory or Azure Synapse Pipelines
- Optimizing queries with Dedicated SQL Pools in Azure Synapse
- Analysing and Optimizing Data Warehouse Storage
- Supporting Hybrid Transactional Analytical Processing (HTAP)
- Performing end-to-end security with Azure Synapse Analytics
- Performing real-time Stream Processing with Stream Analytics
- Creating a Stream Processing Solution with Hubs and Databricks
- Building reports using Power BI integration
- Performing Integrated Machine Learning Processes
The course, along with MS Learn, is designed to help delegates get an understanding of the topics covered on the DP-203 certification exam.
Special discounted pricing for Vuzion Partners can be found on the price guide within the Vuzion Partner portal here or quoted by your BDM. You can also reach out to us at email@example.com
This course is constituted as follows
- Theoretical: 30%
- Practical - Demo: 20%
- Practical - Tasks, Activities or Labs: 50%
Percentages are approximate. Whilst we endeavor to include a blend of theory, demo and activities in all of our courses we recognise that some delegates prefer a particular style of course (I.e. wholly or predominantly lab based workshops or immersion experiences) and would ask them to consider their preferred learning style before registration. We would also ask delegates to check the site regularly for new courses as we expand to offer different blends of theory/practice
Who Should Attend?
Course Level: 300. This course is designed for 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 data analysts and data scientists who work with analytical solutions built on Microsoft Azure.
Roles Aimed at: Data Architects, Data Engineers, Data Scientists or any Data, Business Intelligence or IT professional interested in the field of data engineering, looking to consolidate their deep knowledge, or looking to certify.
The course is designed with technical and analytical backgrounds.
This course is not intended for:
- Inexperienced users in the field of Data Engineering
- Inexperienced users of Azure
- Non-technical or non-analytical roles
Certifications & Competencies
This course is linked to exam DP-203 Data Engineering on Microsoft Azure. For Microsoft Partners, this exam is linked to the Data Platform competency
Exam is not included in the cost of the course and should be paid for separately.
This course has the following prerequisites:
- A modern laptop/desktop
- A modern browser (Edge/Chrome)
- A good internet connection (wired recommended)
Delegates will ideally
- Have passed Azure Fundamentals (AZ-900)
- Have passed Azure Data Fundamentals (DP-900)
- Will have hands on experience with subject matter in this course including Azure, SQL, Data Factory, Synapse and Databricks
Should you have any question related to this course, please do not hesitate to contact us at firstname.lastname@example.org
Upon submission, we will reach out and work with you to find the next available course to fit your schedule
Register today!Limited spaces available
Modules covered include:
- Explore compute and storage options for data engineering workloads.
- Design and implement the serving layer.
- Data engineering considerations for source files
- Run interactive queries using Azure Synapse Analytics serverless SQL pools.
- Explore, transform, and load data into the Data Warehouse using Apache Spark
- Data exploration and transformation in Azure Databricks
- Ingest and load data into the data warehouse.
- Transform data with Azure Data Factory or Azure Synapse Pipelines
- Orchestrate data movement and transformation in Azure Synapse Pipelines
- Optimize query performance with dedicated SQL pools in Azure Synapse
- Analyse and Optimize Data Warehouse Storage
- Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
- End-to-end security with Azure Synapse Analytics
- Real-time Stream Processing with Stream Analytics
- Create a Stream Processing Solution with Event Hubs and Azure Databricks
- Build reports using Power BI integration with Azure Synapse Analytics
- Perform Integrated Machine Learning Processes in Azure Synapse Analytics
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