MS-DP-500T00 - Microsoft Azure Enterprise Data Analyst

This course covers methods and practices for performing advanced data analytics at scale. Students will build on existing analytics experience and will learn to implement and manage a data analytics environment, query and transform data, implement and manage data models, and explore and visualize data. In this course, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.

Student Testimonials

Instructor did a great job, from experience this subject can be a bit dry to teach but he was able to keep it very engaging and made it much easier to focus. Student
Excellent presentation skills, subject matter knowledge, and command of the environment. Student
Instructor was outstanding. Knowledgeable, presented well, and class timing was perfect. Student

Click here to print this page »

Prerequisites


Before attending this course, it is recommended that students have:
A foundational knowledge of core data concepts and how they’re implemented using Azure data services. For more information see Microsoft Certified: Azure Data Fundamentals.
Experience designing and building scalable data models, cleaning and transforming data, and enabling advanced analytic capabilities that provide meaningful business value using Microsoft Power BI. For more information see Microsoft Certified: Data Analyst Associate.

Detailed Class Syllabus


Module 1: Introduction to data analytics on Azure


Explore Azure data services for modern analytics
Understand concepts of data analytics
Explore data analytics at scale

Module 2: Govern data across an enterprise


Introduction to Microsoft Purview
Discover trusted data using Microsoft Purview
Catalog data artifacts by using Microsoft Purview
Manage Power BI artifacts by using Microsoft Purview

Module 3: Model, query, and explore data in Azure Synapse


Introduction to Azure Synapse Analytics
Implement star schema design and query relational data in Azure
Analyze data with a serverless SQL pool in Azure Synapse Analytics
Optimize data warehouse query design
Analyze data with a Spark Pool in Azure Synapse Analytics

Module 4: Prepare data for tabular models in Power BI


Choose a Power BI model framework
Understand scalability in Power BI
Optimize Power Query for scalable solutions
Create and manage scalable Power BI dataflows

Module 5: Design and build scalable tabular models


Create Power BI model relationships
Enforce model security
Implement DirectQuery
Create calculation groups

Module 6: Optimize enterprise-scale tabular models


Optimize performance using Synapse and Power BI
Improve query performance with hybrid tables, dual storage mode, and aggregations
Use tools to optimize Power BI performance

Module 7: Implement advanced data visualization techniques by using Power BI


Understand advanced data visualization concepts
Customize core data models
Monitor data in real-time with Power BI
Create and distribute paginated reports in Power BI report builder

Module 8: Implement and manage an analytics environment


Recommend Power BI administration settings
Recommend a monitoring and auditing solution for a data analytics environment
Configure and manage Power BI capacity
Establish a data access infrastructure in Power BI

Module 9: Manage the analytics development lifecycle


Recommend a deployment strategy for Power BI assets
Recommend a source control strategy for Power BI assets
Perform impact analysis of downstream dependencies from dataflows and datasets
Recommend automation solutions for the analytics development lifecycle, including Power BI REST API
Deploy and manage datasets by using the XMLA endpoint
Deploy reusable assets

Module 10: Integrate an analytics platform into an existing IT infrastructure


Recommend and configure a Power BI tenant or workspace
Identify requirements for a solution, including features, performance, and licensing strategy
Integrate an existing Power BI workspace into Azure Synapse Analytics