This course is designed to give the learners instruction on the SQL dedicated and serverless Spark pools and providing instruction of data wrangling and the ELT process using Synapse Pipelines which is very similar to those familiar with Azure Data Factory (ADF) to move data into the Synapse dedicated pool database.
After completing this course, students will be able to:
Identify the business problems that Azure Synapse Analytics addresses
Describe core capabilities of Azure Synapse Analytics
Determine when to use Azure Synapse Analytics
Identify capabilities and use cases for serverless SQL pools in Azure Synapse Analytics
Query CSV, JSON, and Parquet files using a serverless SQL pool
Create external database objects in a serverless SQL pool
Identify core features and capabilities of Apache Spark
Configure a Spark pool in Azure Synapse Analytics
Run code to load, analyse, and visualise data in a Spark notebook
Describe core features and capabilities of Delta Lake
Create and use Delta Lake tables in a Synapse Analytics Spark pool
Create Spark catalog tables for Delta Lake data
Use Delta Lake tables for streaming data
Query Delta Lake tables from a Synapse Analytics SQL pool
Design a schema for a relational data warehouse
Create fact, dimension, and staging tables
Use SQL to load data into data warehouse tables
Use SQL to query relational data warehouse tables
Describe core concepts for Azure Synapse Analytics pipelines
Create a pipeline in Azure Synapse Studio
Implement a data flow activity in a pipeline
Initiate and monitor pipeline runs
Lumify Work has been delivering effective training across all Microsoft products for over 30 years. We are proud to be both Australia's and New Zealand’s first Microsoft Gold Learning Solutions Partner and the winner of the Microsoft MCT Superstars Award for FY24, which formally recognises us as having the highest quality Microsoft Certified Trainers (MCTs) in ANZ. All Lumify Work Microsoft Azure courses follow Microsoft Official Curriculum (MOC) and are led by MCTs.
Data Analyst
Data Engineer
Familiarity with notebooks that use different languages and a Spark engine, such as Databricks, Jupyter Notebooks, Zeppelin notebooks and more.
Some experience with SQL, Python, and Azure tools, such as Data Factory.
The supply of this course by Lumify Work is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.
