The Advanced Analytics in Azure training course introduces students to the Azure data processing and analysis services necessary to build an end-to-end analytics pipeline and solution. Microsoft Azure offers Azure Synapse Analytics, a fully managed, elastic data warehouse with security at every level of scale. This course will review the different scenarios for gathering, storing, processing, and analyzing data both on-demand and in real-time to gain deep insights into your data.
The course begins with students learning more about Azure Synapse Analytics as a data store to build out a data warehouse and further dive into tools such as Azure Data Factory, Azure Data Lake Storage, Azure Databricks, Azure Machine Learning and more. Next, there will be practical application of these tools and students will learn how to store and process both structured and unstructured data, stream data using Apache Kafka on Azure HDInsight and use AutoML within Azure Machine Learning. Finally, Power BI will be introduced so that students get an understanding of how they can visualize and present data insights to end users.
Purpose
|
Learn to build end-to-end data applications using Microsoft Azure and understand which tools are best suited to certain problems and use-cases. |
Audience
|
Software Developers, Data Scientists and Data Engineers who want to learn more about building end to end analytic applications on Microsoft Azure. |
Role
| Data Engineer - Data Scientist - Software Developer |
Skill Level
| Advanced |
Style
| Targeted Topic - Workshops |
Duration
| 3 Days |
Related Technologies
| Power BI | Azure |
Productivity Objectives
- Explain what Azure Synapse Analytics is and how to use other complementary services with it.
- Define the key aspects of big data for data processing including how to process structured and unstructured data.
- Identify the key concepts and services for ingesting, storing, preparing, and analyzing data.
- Build and implement an end-to-end data analytic solution.
