This course will teach students about data engineering with an emphasis on leveraging Azure data platform tools to deal with batch and real-time analytical solutions. The fundamental computing and storage technologies that are needed to construct an analytical solution will be first understood by the students. The ability to interactively examine data contained in files inside a data lake will be taught to the pupils. They will discover how to ingest using Azure Data Factory or Azure Synapse pipelines, or how to import data utilizing the Apache Spark feature available in Azure Synapse Analytics or Azure Databricks. Using the same tools that are used to input data, the students will also learn about the several ways they might alter the data.
You should have subject matter expertise in integrating, transforming, and consolidating data from various structured, unstructured, and streaming data systems into a suitable schema for building analytics solutions. You must have solid knowledge of data processing languages, including:
You need to understand parallel processing and data architecture patterns. You should be proficient in using the following to create data processing solutions:
Topic 1: Data storage
Topic 2: Data processing
Topic 3: Data storage and data processing