Descripción
OBJETIVOS DEL CURSO
After completing this course, students will be able to
- Explore compute and storage options for data engineering workloads in Azure
- Design and Implement the serving layer
- Understand data engineering considerations
- Run interactive queries using serverless SQL pools
- Explore, transform, and load data into the Data Warehouse using Apache Spark
- Perform 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
- Integrate Data from Notebooks with Azure Data Factory or Azure Synapse Pipelines
- Optimize Query Performance with Dedicated SQL Pools in Azure Synapse
- Analyze and Optimize Data Warehouse Storage
- Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
- Perform end-to-end security with Azure Synapse Analytics
- Perform 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 Synapase Analytics
- Perform Integrated Machine Learning Processes in Azure Synapse Analytics
QUIENES DEBEN ASISTIR
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 data analysts and data scientists who work with analytical solutions built on Microsoft Azure.
PRERREQUISITOS
Successful students start this course with knowledge of cloud computing and core data concepts and professional experience with data solutions.
Specifically completing:
- Microsoft Azure Fundamentals
- Microsoft Azure Data Fundamentals
CALENDARIO
Duración de curso, 4 días.
Mayo 23-Jun 1, 2022.
Julio 5-8, 2022, 2022.
Octubre 11-14, 2022.
MÁS INFORMACIÓN
Curso en línea Guiado por un Instructor.