Course Overview

This course is scheduled to retire on April 30, 2024.

This DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI 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 DP-500 training, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.

Training Exclusives

Live instructor-led interactive sessions with Microsoft Certified Trainers (MCT).
Access to Microsoft Official Courseware (MOC).
Real-time Virtual Lab Environment.
Experience 24*7 Learner Support.
Self-paced learning and flexible schedules.

Mode of Training

🏫 Classroom 💻 Live Online 🧪 Blended 👨‍👩‍👧‍👦 Private Group

What you will learn

Data transformation and query
Manage and implement data models
Investigate and display data
Setup and administration of a data analytics environment

Who Should Attend This Course?

Candidates should have experience designing, developing, and deploying enterprise-scale data analytics solutions. Candidates should specifically possess extensive Power BI skills, including maintaining data repositories, processing data both on- and offline, and working with Power Query and Data Analysis Expressions (DAX).
Additionally, they should be adept in consuming data from Azure Synapse Analytics and have knowledge of querying relational databases, using Transact-SQL (T-SQL) to analyze data, and visualizing data.

Prerequisites

Required

A fundamental understanding of basic data ideas and how to use Azure data services to implement them.
Experience utilizing Microsoft Power BI to enable powerful analytical capabilities that deliver meaningful business value, clean and convert data, and construct scalable data models.

📞 Talk to a Learning Advisor

📘 DP-500T00: Designing and Implementing Enterprise-Scale Analytics Solutions Using Microsoft Azure and Microsoft Power BI Outline

Describe the Azure data ecosystem for analytics

Describe types of data analytics
Understand the data analytics process

Explore data job roles in analytics
Understand tools for scaling analytics solutions

Evaluate whether Microsoft Purview is appropriate for data discovery and governance needs.
Describe how the features of Microsoft Purview work to provide data discovery and governance.

Browse, search, and manage data catalog assets.
Use data catalog assets with Power BI.
Use Microsoft Purview in Azure Synapse

Describe asset classification in Microsoft Purview.

Register and scan a Power BI tenant.
Use the search and browse functions to find data assets.
Describe the schema details and data lineage tracing of Power BI data assets.

Catalog Azure Synapse Analytics database assets in Microsoft Purview.
Configure Microsoft Purview integration in Azure Synapse Analytics.
Search the Microsoft Purview catalog from Synapse Studio.
Track data lineage in Azure Synapse Analytics pipelines activities.

Identify the business problems that Azure Synapse Analytics addresses.
Describe core capabilities of Azure Synapse Analytics.
Determine when to use Azure Synapse Analytics.

Identify capabilities and use cases for serverless SQL pools in Azure Synapse Analytics
Query CSV, JSON, and Parquet files using a serverless SQL pool
Create external database objects in a serverless SQL pool

Identify core features and capabilities of Apache Spark.
Configure a Spark pool in Azure Synapse Analytics.
Run code to load, analyze, and visualize data in a Spark notebook.

Design a schema for a relational data warehouse.
Create fact, dimension, and staging tables.
Use SQL to load data into data warehouse tables.
Use SQL to query relational data warehouse tables.

Describe Power BI model fundamentals.
Determine when to develop an import model.
Determine when to develop a DirectQuery model.
Determine when to develop a composite model.
Choose an appropriate Power BI model framework.

Describe the importance of building scalable data models
Implement Power BI data modeling best practices
Use the Power BI large dataset storage format

Describe Power BI dataflows and use cases.
Describe best practices for implementing Power BI dataflows.
Create and consume Power BI dataflows.

Understand how model relationship work.
Set up relationships.
Use DAX relationship functions.
Understand relationship evaluation.

Define time intelligence.
Use common DAX time intelligence functions.
Create useful intelligence calculations.

Explore how calculation groups work.
Maintain calculation groups in a model.
Use calculation groups in a Power BI report.

Restrict access to Power BI model data with RLS.
Restrict access to Power BI model objects with OLS.
Apply good development practices to enforce Power BI model security.

Optimize queries using performance analyzer.
Troubleshoot DAX performance using DAX Studio.
Optimize a data model using Tabular Editor.

Create and import a custom report theme.
Create custom visuals with R or Python.
Enable personalized visuals in a report.
Review report performance using Performance Analyzer.
Design and configure Power BI reports for accessibility.

Describe Power BI real-time analytics.
Set up automatic page refresh.
Create real-time dashboards.
Set up auto-refresh paginated reports.

Get data.
Create a paginated report.
Work with charts and tables on the report.
Publish the report.

Define the key components of an effective BI governance model
Describe the key elements associated with data governance
Configure, deploy, and manage elements of a BI governance strategy
Set up BI help and support settings

Understand the differences between My workspace, workspaces, and apps
Describe new workspace capabilities and how they improve the user experience
Anticipate migration impact to Power BI users
Share, publish to the web, embed links and secure Power BI reports, dashboards, and content

Discover what usage metrics are available through the Power BI admin portal
Optimize use of usage metrics for dashboards and reports
Distinguish between audit logs and the activity logs

Describe the difference between Power BI Pro and Power BI Premium
Define dataset eviction
Explain how Power BI manages memory resources
List three external tools you can use with Power BI Premium.

Understand the difference between gateways, the various connectivity modes, and data refresh methods.
Describe the gateway network requirements, where to place the gateway in your network, and how to use clustering to ensure high availability.
Scale, monitor, and manage gateway performance and users.

Describe the various embedding scenarios that allow you to broaden the reach of Power BI
Understand the options for developers to customize Power BI solutions
Learn to provision and optimize Power BI embedded capacity and create and deploy dataflows
Build custom Power BI solutions template apps