• Classroom
  • Online, Instructor-Led
Course Description

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.

Learning Objectives

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 Check your knowledge 25 – Facilitate collaboration and sharing in Power BI Workspaces evolved Impact to Power BI users Permissions in workspaces v2 Apps in Power BI Share Publish to web Embed and link in portals Data sensitivity labels Data privacy 26 – Monitor and audit usage Usage metrics for dashboards and reports Usage metrics for dashboards and reports – new version Audit logs Activity log 27 – Provision Premium capacity in Power BI Premium resource management Supporting multi geographies Bring your own key (BYOK) Featured external tools 28 – Establish a data access infrastructure in Power BI Personal gateways versus enterprise gateways How data is refreshed Gateway network requirements Where to install gateway? Establish high availability gateways Establish load balancing of gateways Gateway performance monitoring documentation Multiple data sources per gateway Manage gateway users Active Directory user mapping with custom property lookup 29 – 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 30 – Automate Power BI administration REST API – Power BI service Microsoft Power BI cmdlets for Windows PowerShell and PowerShell core Install and use the Power BI cmdlet Test REST API calls Script typical administrator tasks 31 – 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 32 – Design a Power BI application lifecycle management strategy Define application lifecycle management Use workspaces to manage application lifecycle Export and import Power BI solutions Configure deployment pipelines 33 – 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 34 – 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

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Cyber Defense Analysis
  • Cyber Defense Infrastructure Support
  • Cyber Investigation
  • Digital Forensics
  • Exploitation Analysis
  • Network Services
  • Risk Management
  • Software Development
  • Test and Evaluation
  • Threat Analysis
  • Training, Education, and Awareness
  • Vulnerability Assessment and Management