In this course, you will learn about the data engineering as it pertains to working with batch and real-time analytical solutions using Azure data platform technologies.
You will begin by understanding the core compute and storage technologies that are used to build an analytical solution. You will also learn how to interactively explore data stored in files in a data lake. You will learn the various ingestion techniques that can be used to load data using the Apache Spark capability found in Azure Synapse Analytics or Azure Databricks, or how to ingest using Azure Data Factory or Azure Synapse pipelines.
You will also learn the various ways they can transform the data using the same technologies that is used to ingest data. You will understand the importance of implementing security to ensure that the data is protected at rest or in transit. You will then show how to create a real-time analytical system to create real-time analytical solutions.
Module 1: Explore compute and storage options for data engineering workloads
Module 2: Run interactive queries using Azure Synapse Analytics serverless SQL pools
Module 3: Data exploration and transformation in Azure Databricks
Module 4: Explore, transform, and load data into the Data Warehouse using Apache Spark
Module 5: Ingest and load data into the data warehouse
Module 6: Transform data with Azure Data Factory or Azure Synapse Pipelines
Module 7: Orchestrate data movement and transformation in Azure Synapse Pipelines
Module 8: End-to-end security with Azure Synapse Analytics
Module 9: Support Hybrid Transactional Analytical Processing (HTAP) with Azure Synapse Link
Module 10: Real-time Stream Processing with Stream Analytics
Module 11: Create a Stream Processing Solution with Event Hubs and Azure Databricks
Official Microsoft Labs
Du lundi au vendredi, de 8:30 à 18:00.
Monday to Friday, from 8:30 am to 06:00 pm.
