This four-day 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 visualise data. In this course, students will use Microsoft Purview, Azure Synapse Analytics, and Power BI to build analytics solutions.
Microsoft DP-500T00 - Designing and Implementing Enterprise-Scale Analytics Solutions Using Azure and Power BI
- Length 4 days
- Version A
- Register interest
Why study this course
Aligns to certification
What you’ll learn
Implement and manage a data analytics environment
Query and transform data
Implement and manage data models
Explore and visualise data
Microsoft Azure at DDLS
DDLS is your best choice for training and certification in any of Microsoft’s leading technologies and services. We’ve been delivering effective training across all Microsoft products for over 30 years, and are proud to be Australia’s First and largest Microsoft Gold Learning Solutions Partner. All DDLS Microsoft courses follow Microsoft Official Curriculum (MOC) and are led by Microsoft Certified Trainers. Join more than 5,000 students who attend our quality Microsoft courses every year.
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No matter your chosen technologies or platforms, we can help you stay one step ahead.
Who is the course for?
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, analysing data by using Transact-SQL (T-SQL), and visualising 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.
Explore Azure data services for modern analytics
Understand concepts of data analytics
Explore data analytics at scale
Module 2: Govern data across an enterprise
This module explores the role of an enterprise data analyst in organisational 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.
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
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.
Introduction to Azure Synapse Analytics
Use Azure Synapse serverless SQL pool to query files in a data lake
Analyse data with Apache Spark in Azure Synapse Analytics
Analyse data in a relational data warehouse
Lab : Query data in Azure
Lab : Create a star schema model
Lab : Explore data in Spark notebooks
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 optimisation techniques, and the implementation of Power BI dataflows.
Choose a Power BI model framework
Understand scalability in Power BI
Optimise Power Query for scalable solutions
Create and manage scalable Power BI dataflows
Lab : Create a dataflow
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.
Create Power BI model relationships
Enforce model security
Create calculation groups
Use tools to optimise Power BI performance
Lab : Create model relationships
Lab : Design and build tabular models
Lab : Create calculation groups
Lab : Use tools to optimise Power BI performance
Lab : Enforce model security
Module 6: Implement advanced data visualisation techniques by using Power BI
This module explores data visualisation concepts including accessibility, customisation of core data models, real-time data visualisation, and paginated reporting.
Understand advanced data visualisation concepts
Customise core data models
Monitor data in real-time with Power BI
Create and distribute paginated reports in Power BI report builder
Lab : Create and distribute paginated reports in Power BI Report Builder
Lab : Monitor data in real-time with Power BI
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.
Provide governance in a Power BI environment
Facilitate collaboration and sharing in Power BI
Monitor and audit usage
Provision Premium capacity in Power BI
Establish a data access infrastructure in Power BI
Broaden the reach of Power BI
Automate Power BI administration
Build reports using Power BI within Azure Synapse Analytics
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.
Design a Power BI application lifecycle management strategy
Create and manage a Power BI deployment pipeline
Create and manage Power BI assets
Lab : Create reusable Power BI assets
Module 9: Integrate an analytics platform into an existing IT infrastructure
This module explores the integration of a Power BI analytics solution into existing Azure infrastructure. Students will understand Power BI tenant and workspace configurations, along with considerations for Power BI deployment in an organisation.
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
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 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 Power BI Data Analyst.
Terms & Conditions
The supply of this course by DDLS is governed by the booking terms and conditions. Please read the terms and conditions carefully before enrolling in this course, as enrolment in the course is conditional on acceptance of these terms and conditions.