DP-500T00 Designing and Implementing Enterprise-Scale Analytics Using Azure and Power BI

Price
$2,380.00 USD

Duration
4 Days

 

Delivery Methods
Virtual Instructor Led
Private Group

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Course Overview

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.

Who Should Attend?

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.

  • Top-rated instructors: Our crew of subject matter experts have an average instructor rating of 4.8 out of 5 across thousands of reviews.
  • Authorized content: We maintain more than 35 Authorized Training Partnerships with the top players in tech, ensuring your course materials contain the most relevant and up-to date information.
  • Interactive classroom participation: Our virtual training includes live lectures, demonstrations and virtual labs that allow you to participate in discussions with your instructor and fellow classmates to get real-time feedback.
  • Post Class Resources: Review your class content, catch up on any material you may have missed or perfect your new skills with access to resources after your course is complete.
  • Private Group Training: Let our world-class instructors deliver exclusive training courses just for your employees. Our private group training is designed to promote your team’s shared growth and skill development.
  • Tailored Training Solutions: Our subject matter experts can customize the class to specifically address the unique goals of your team.

Learning Credits: Learning Credits can be purchased well in advance of your training date to avoid having to commit to specific courses or dates. Learning Credits allow you to secure your training budget for an entire year while eliminating the administrative headache of paying for individual classes. They can also be redeemed for a full year from the date of purchase. If you have previously purchased a Learning Credit agreement with New Horizons, you may use a portion of your agreement to pay for this class.

If you have questions about Learning Credits, please contact your Account Manager.

Corporate Tech Pass: Our Corporate Tech Pass includes unlimited attendance for a single person, in the following Virtual Instructor Led course types: Microsoft Office, Microsoft Technical, CompTIA, Project Management, SharePoint, ITIL, Certified Ethical Hacker, Certified Hacking Forensics Investigator, Java, Professional Development Courses and more. The full list of eligible course titles can be found at https://www.newhorizons.com/eligible.

If you have questions about our Corporate Tech Pass, please contact your Account Manager.

Course Prerequisites

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.

Agenda

1 - Explore Azure data services for modern analytics

  • Understand the Azure data ecosystem
  • Explore modern analytics solution architecture

2 - Understand concepts of data analytics

  • Understand data analytics types
  • Explore the data analytics process
  • Understand types of data and data storage

3 - Explore data analytics at scale

  • Explore data team roles and responsibilities
  • Review tasks and tools for data analysts
  • Scale analytics with Azure Synapse Analytics and Power BI
  • Strategies to scale analytics

4 - Introduction to Microsoft Purview

  • What is Microsoft Purview?
  • How Microsoft Purview works
  • When to use Microsoft Purview

5 - Discover trusted data using Microsoft Purview

  • Search for assets
  • Browse assets
  • Use assets with Power BI
  • Integrate with Azure Synapse Analytics

6 - Catalog data artifacts by using Microsoft Purview

  • Register and scan data
  • Classify and label data
  • Search the data catalog

7 - Manage Power BI assets by using Microsoft Purview

  • Register and scan a Power BI tenant
  • Search and browse Power BI assets
  • View Power BI metadata and lineage

8 - Integrate Microsoft Purview and Azure Synapse Analytics

  • Catalog Azure Synapse Analytics data assets in Microsoft Purview
  • Connect Microsoft Purview to an Azure Synapse Analytics workspace
  • Search a Purview catalog in Synapse Studio
  • Track data lineage in pipelines

9 - Introduction to Azure Synapse Analytics

  • What is Azure Synapse Analytics
  • How Azure Synapse Analytics works
  • When to use Azure Synapse Analytics

10 - Use Azure Synapse serverless SQL pool to query files in a data lake

  • Understand Azure Synapse serverless SQL pool capabilities and use cases
  • Query files using a serverless SQL pool
  • Create external database objects

11 - Analyze data with Apache Spark in Azure Synapse Analytics

  • Get to know Apache Spark
  • Use Spark in Azure Synapse Analytics
  • Analyze data with Spark
  • Visualize data with Spark

12 - Analyze data in a relational data warehouse

  • Design a data warehouse schema
  • Create data warehouse tables
  • Load data warehouse tables
  • Query a data warehouse

13 - Choose a Power BI model framework

  • 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 a model framework

14 - Understand scalability in Power BI

  • Describe the significance of scalable models
  • Implement Power BI data modeling best practices
  • Configure large datasets

15 - Create and manage scalable Power BI dataflows

  • Define use cases for dataflows
  • Create reusable assets
  • Implement best practices

16 - Create Power BI model relationships

  • Understand model relationships
  • Set up relationships
  • Use DAX relationship functions
  • Understand relationship evaluation

17 - Use DAX time intelligence functions in Power BI Desktop models

  • Use DAX time intelligence functions
  • Additional time intelligence calculations

18 - Create calculation groups

  • Understand calculation groups
  • Explore calculation groups features and usage
  • Create calculation groups in a model

19 - Enforce Power BI model security

  • Restrict access to Power BI model data
  • Restrict access to Power BI model objects
  • Apply good modeling practices

20 - Use tools to optimize Power BI performance

  • Use Performance analyzer
  • Troubleshoot DAX performance by using DAX Studio
  • Optimize a data model by using Best Practice Analyzer

21 - Understand advanced data visualization concepts

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

22 - Monitor data in real-time with Power BI

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

23 - Create paginated reports

  • Get data
  • Create a paginated report
  • Work with charts on the report
  • Publish the report

24 - Provide governance in a Power BI environment

  • Elements of data governance
  • Configure tenant settings
  • Deploy organizational visuals
  • Manage embed codes
  • Help and support settings

25 - Monitor and audit usage

  • Usage metrics for dashboards and reports
  • Usage metrics for dashboards and reports - new version
  • Audit logs
  • Activity log

26 - Broaden the reach of Power BI

  • REST API custom development
  • Provision a Power BI embedded capacity
  • Dataflow introduction
  • Dataflow explained
  • Create a Dataflow
  • Dataflow capabilities on Power BI Premium
  • Template apps - install packages
  • Template apps - installed entities
  • Template app governance

27 - Build reports using Power BI within Azure Synapse Analytics

  • Describe the Power BI and Synapse workspace integration
  • Understand Power BI data sources
  • Describe Power BI optimization options
  • Visualize data with serverless SQL pools

28 - Design a Power BI application lifecycle management strategy

  • Define application lifecycle management
  • Recommend a source control strategy
  • Design a deployment strategy

29 - Create and manage a Power BI deployment pipeline

  • Understand the deployment process
  • Create a deployment pipeline
  • Assign a workspace
  • Deploy content
  • Work with deployment pipelines

30 - Create and manage Power BI assets

  • Create reusable Power BI assets
  • Explore Power BI assets using lineage view
  • Manage a Power BI dataset using XMLA endpoint
 

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