DP-500: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI

Length: 4 Day(s)     Cost:$3200 + GST

= Scheduled class     = Guaranteed to run     = Fully booked

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LOCATION April May June July
Virtual Class
This course will provide you with a broad introduction to the finance and operations capabilities of Dynamics 365. You will become familiar with the concept of enterprise resource management (ERP), as well as each of the finance and operations apps, including Dynamics 365 Supply Chain Management, Dynamics 365 Finance, Dynamics 365 Commerce , Dynamics 365 Human Resources, and the ERP capabilities of Dynamics 365 Project Operations. This course will include lecture as well as hands-on-labs.

Candidates for this course should have subject matter expertise in designing, creating, and deploying enterprise-scale data analytics solutions. Specifically, candidates should have advanced Power BI skills, including managing data repositories and data processing in the cloud and on-premises, along with using Power Query and Data Analysis Expressions (DAX). They should also be proficient in consuming data from Azure Synapse Analytics and should have experience querying relational databases, analyzing data by using Transact-SQL (T-SQL), and visualizing data.

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. This is covered in our Microsoft Azure Data Fundamentals course.

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. This is covered in our Microsoft Power BI Data Analyst course.

After completing this course, students will be able to:
  • Implement and manage a data analytics environment
  • Query and transform data
  • Implement and manage data models
  • Explore and visualize data

Module 1: Introduction to data analytics on Azure

This module explores key concepts of data analytics, including types of analytics, data, and storage. Students will explore the analytics process and tools used to discover insights and learn about the responsibilities of an enterprise data analyst and what tools are available to build scalable solutions.

After completing this module, students will be able to:

  • Describe types of data analytics
  • Understand the data analytics process
  • Define data job roles in analytics
  • Understand tools for scaling analytics solutions

Module 2: Govern data across an enterprise

This module explores the role of an enterprise data analyst in organizational data governance. Students will explore the use of Microsoft Purview to register and catalog data assets, to discover trusted assets for reporting, and to scan a Power BI environment.

After completing this module, students will be able to:

  • Browse, search, and manage data catalog assets.
  • Use data catalog assets with Power BI.
  • Use Microsoft Purview in Azure Synapse Studio.
  • Register and scan a Power BI environment using Microsoft Purview.

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

This module explores the use of Azure Synapse Analytics for exploratory data analysis. Students will explore the capabilities of Azure Synapse Analytics including the basics of data warehouse design, querying data using T-SQL, and exploring data using Spark notebooks.

After completing this module, students will be able to:

  • Understand when to use Azure Synapse Analytics in reporting solutions.
  • Query data with SQL.
  • Query data with Spark.

Module 4: Prepare data for tabular models in Power BI

This module explores the fundamental elements of preparing data for scalable analytics solutions using Power BI. Students will explore model frameworks, considerations for building data models that will scale, Power Query optimization techniques, and the implementation of Power BI dataflows.

After completing this module, students will be able to:

  • Choose an appropriate Power BI model framework.
  • Optimize Power Query.
  • Create and manage scalable Power BI dataflows.

Module 5: Design and build scalable tabular models

This module explores the critical underlying aspects of tabular modeling for building Power BI models that can scale. Students will learn about model relationships and model security, working with direct query, and using calculation groups.

After completing this module, students will be able to:

  • Understand and create Power BI model relationships.
  • Design and enforce Power BI model security.
  • Design and build scalable tabular models.
  • Create calculation groups.

Module 6: Implement advanced data visualization techniques by using Power BI

This module explores data visualization concepts including accessibility, customization of core data models, real-time data visualization, and paginated reporting.

After completing this module, students will be able to:

  • Understand and apply advanced data visualization concepts including accessibility.
  • Troubleshoot report performance issues.
  • Use real-time visuals in Power BI.
  • Create and distribute paginated reports.

Module 7: Implement and manage an analytics environment

This module explores key considerations for implementing and managing Power BI. Students will understand key recommendations for administration and monitoring of Power BI, including configuration and management of Power BI capacity.

After completing this module, students will be able to:

  • Recommend Power BI administration settings.
  • Recommend a monitoring and auditing solution for a data analytics environment.
  • Configure and manage Power BI capacity.

Module 8: Manage the analytics development lifecycle

This module explores considerations for deployment, source control, and application lifecycle management of analytics solutions. Students will understand what to recommend and will be able to deploy and manage automated and reusable Power BI assets.

After completing this module, students will be able to:

  • Recommend strategies for Power BI deployment and source control.
  • Recommend automation solutions for the analytics development lifecycle.