Skip to main content

AZURE DATA PLATFORM LAB DP200


Cloudstreet

About This Course

In this Course you will learn about the main concepts related to advanced analytics and Big Data processing and how Azure Data Services can be used to implement a modern data warehouse architecture. You will learn what Azure services you can leverage to establish a solid data platform to quickly ingest, process and visualise data from a large variety of data sources. Along with the real-life scenarios and data source, this course is designed to progressively implement an extended modern data platform architecture starting from a traditional relational data pipeline. You’ll explore big data scenarios with large data files and distributed computing. Then we introduce big data scenarios with large data files and distributed computing. We add non-structured data and AI into the mix and finish off with real-time stream analytics. You will have done all of that by the end of the workshop. While the course is designed on self-paced learning model, the ideal time to learn and practice all the labs is nearly 16 hours. What you’ll learn Modern Data warehousing and processing concepts. Hands on training on Azure data platform technologies and services including Storage explorer, SQL server, Databricks, Data Factory, Synapse Analytics and more. Visualising the processed data using Power BI.

Requirements

1. An Azure account with the credit of nearly AUD $150. 2. Candidates should be familiar with the generic concepts of Azure cloud services. 3. Basic understanding of the general technology concepts, including concepts of networking, storage, compute, application support, and application development.

Course Instructors

Course Staff Image #1

Yuba Panta

Certified Azure Instructor

Course Staff Image #2

Peter O'Gorman

Certified Instructor with Industry Experience

Frequently Asked Questions

How can I get access to this courtse?

Please email to arif@cloudst.com.au for course access.

See our list of supported browsers for the most up-to-date information.

Enroll