Implement a Data Analytics Solution with Azure Synapse Analytics

  • Learning Path
  • 6 Modules
Intermediate
Data Engineer
Azure Synapse Analytics

Prerequisites

The Audience should have familiarity with notebooks that use different languages and a Spark engine, such as Databricks, Jupyter Notebooks, Zeppelin notebooks and more. They should also have some experience with SQL, Python, and Azure tools, such as Data Factory.

Modules in this learning path

Introduction to Azure Synapse Analytics

Learn about the features and capabilities of Azure Synapse Analytics - a cloud-based platform for big data processing and analysis.

Use Azure Synapse serverless SQL pool to query files in a data lake

With Azure Synapse serverless SQL pool, you can leverage your SQL skills to explore and analyze data in files, without the need to load the data into a relational database.

Analyze data with Apache Spark in Azure Synapse Analytics

Apache Spark is a core technology for large-scale data analytics. Learn how to use Spark in Azure Synapse Analytics to analyze and visualize data in a data lake.

Use Delta Lake in Azure Synapse Analytics

Delta Lake is an open source relational storage area for Spark that you can use to implement a data lakehouse architecture in Azure Synapse Analytics.

Analyze data in a relational data warehouse

Relational data warehouses are a core element of most enterprise Business Intelligence (BI) solutions, and are used as the basis for data models, reports, and analysis.

Build a data pipeline in Azure Synapse Analytics

Pipelines are the lifeblood of a data analytics solution. Learn how to use Azure Synapse Analytics pipelines to build integrated data solutions that extract, transform, and load data across diverse systems.