Course Catalog
Microsoft Power BI Data Analyst (PL-300T00)
Code: PL-300T00
Duration: 3 Day
$2095 USD

OVERVIEW

The course will show how to access and process data from a range of data sources including both relational and non-relational sources. Finally, this course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.

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DELIVERY FORMAT

This course is available in the following formats:

Virtual Classroom

Duration: 3 Day
Classroom

Duration: 3 Day

CLASS SCHEDULE

Delivery Format: Virtual Classroom
Date: Apr 01 2024 - Apr 03 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Apr 08 2024 - Apr 10 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Apr 22 2024 - Apr 24 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: May 06 2024 - May 08 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: May 13 2024 - May 15 2024 | 12:00 - 20:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: May 20 2024 - May 22 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Jun 03 2024 - Jun 05 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Jun 10 2024 - Jun 12 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Jun 24 2024 - Jun 26 2024 | 11:00 - 20:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Jul 08 2024 - Jul 10 2024 | 12:00 - 20:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Jul 29 2024 - Jul 31 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Jul 01 2024 - Jul 03 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Aug 12 2024 - Aug 14 2024 | 12:00 - 20:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Aug 19 2024 - Aug 21 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Aug 26 2024 - Aug 28 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Sep 09 2024 - Sep 11 2024 | 12:00 - 20:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Sep 16 2024 - Sep 18 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Sep 23 2024 - Sep 25 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Oct 07 2024 - Oct 09 2024 | 12:00 - 20:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Oct 21 2024 - Oct 23 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Oct 28 2024 - Oct 30 2024 | 09:00 - 17:00 EDT
Location: Online
Course Length: 3 Day

$ 2095

Delivery Format: Virtual Classroom
Date: Nov 18 2024 - Nov 20 2024 | 09:00 - 17:00 EST
Location: Online
Course Length: 3 Day

$ 2095

GOALS

Students will learn to,

  • Discover data analysis
  • Get started building with Power BI
  • Get data in Power BI
  • Clean, transform, and load data in Power BI
  • Design a semantic model in Power BI
  • Add measures to Power BI Desktop models
  • Add calculated tables and columns to Power BI Desktop models
  • Use DAX time intelligence functions in Power BI Desktop models
  • Optimize a model for performance in Power BI
  • Design Power BI reports
  • Configure Power BI report filters
  • Enhance Power BI report designs for the user experience
  • Perform analytics in Power BI
  • Create and manage workspaces in Power BI
  • Manage semantic models in Power BI
  • Create dashboards in Power BI
  • Implement row-level security
OUTLINE

Module 1 :Discover data analysis

  • Learn about the roles in data.
  • Learn about the tasks of a data analyst.

Module 2 :Get started building with Power BI

  • Learn how Power BI services and applications work together.
  • Explore how Power BI can make your business more efficient.
  • Learn how to create compelling visuals and reports.

Module 3 :Get data in Power BI

  • Identify and connect to a data source
  • Get data from a relational database, like Microsoft SQL Server
  • Get data from a file, like Microsoft Excel
  • Get data from applications
  • Get data from Azure Analysis Services
  • Select a storage mode
  • Fix performance issues
  • Resolve data import errors

Module 4 :Clean, transform, and load data in Power BI

  • Resolve inconsistencies, unexpected or null values, and data quality issues.
  • Apply user-friendly value replacements.
  • Profile data so you can learn more about a specific column before using it.
  • Evaluate and transform column data types.
  • Apply data shape transformations to table structures.
  • Combine queries.
  • Apply user-friendly naming conventions to columns and queries.
  • Edit M code in the Advanced Editor.

Module 5 :Design a semantic model in Power BI

  • Create common date tables
  • Configure many-to-many relationships
  • Resolve circular relationships
  • Design star schemas

Module 6 : Add measures to Power BI Desktop models

  • Determine when to use implicit and explicit measures.
  • Create simple measures.
  • Create compound measures.
  • Create quick measures.
  • Describe similarities of, and differences between, a calculated column and a measure.

Module 7 : Add calculated tables and columns to Power BI Desktop models

  • Create calculated tables.
  • Create calculated columns.
  • Identify row context.
  • Determine when to use a calculated column in place of a Power Query custom column.
  • Add a date table to your model by using DAX calculations.

Module 8 : Use DAX time intelligence functions in Power BI Desktop models

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

Module 9 : Optimize a model for performance in Power BI

  • Review the performance of measures, relationships, and visuals.
  • Use variables to improve performance and troubleshooting.
  • Improve performance by reducing cardinality levels.
  • Optimize DirectQuery models with table level storage.
  • Create and manage aggregations.

Module 10 : Design Power BI reports

  • Learn about the structure of a Power BI report.
  • Learn about report objects.
  • Select the appropriate visual type to use.

Module 11 : Configure Power BI report filters

  • Design reports for filtering.
  • Design reports with slicers.
  • Design reports by using advanced filtering techniques.
  • Apply consumption-time filtering.
  • Select appropriate report filtering techniques.

Module 12 : Enhance Power BI report designs for the user experience

  • Design reports to show details.
  • Design reports to highlight values.
  • Design reports that behave like apps.
  • Work with bookmarks.
  • Design reports for navigation.
  • Work with visual headers.
  • Design reports with built-in assistance.
  • Use specialized visuals.

Module 13 : Perform analytics in Power BI

  • Explore statistical summary.
  • Identify outliers with Power BI visuals.
  • Group and bin data for analysis.
  • Apply clustering techniques.
  • Conduct time series analysis.
  • Use the Analyze feature.
  • Use advanced analytics custom visuals.
  • Review Quick insights.
  • Apply AI Insights.

Module 14 : Create and manage workspaces in Power BI

  • Create and manage Power BI workspaces and items.
  • Distribute a report or dashboard.
  • Monitor usage and performance.
  • Recommend a development lifecycle strategy.
  • Troubleshoot data by viewing its lineage.
  • Configure data protection.

Module 15 : Manage semantic models in Power BI

  • Use a Power BI gateway to connect to on-premises data sources.
  • Configure a scheduled refresh for a semantic model .
  • Configure incremental refresh settings.
  • Manage and promote semantic models.
  • Troubleshoot service connectivity.
  • Boost performance with query caching (Premium).

Module 16 : Create dashboards in Power BI

  • Set a mobile view.
  • Add a theme to the visuals in your dashboard.
  • Configure data classification.
  • Add real-time dataset visuals to your dashboards.
  • Pin a live report page to a dashboard.

Module 17 : Implement row-level security

  • Configure row-level security by using a static method.
  • Configure row-level security by using a dynamic method.

Module 1 :Discover data analysis

  • Learn about the roles in data.
  • Learn about the tasks of a data analyst.

Module 2 :Get started building with Power BI

  • Learn how Power BI services and applications work together.
  • Explore how Power BI can make your business more efficient.
  • Learn how to create compelling visuals and reports.

Module 3 :Get data in Power BI

  • Identify and connect to a data source
  • Get data from a relational database, like Microsoft SQL Server
  • Get data from a file, like Microsoft Excel
  • Get data from applications
  • Get data from Azure Analysis Services
  • Select a storage mode
  • Fix performance issues
  • Resolve data import errors

Module 4 :Clean, transform, and load data in Power BI

  • Resolve inconsistencies, unexpected or null values, and data quality issues.
  • Apply user-friendly value replacements.
  • Profile data so you can learn more about a specific column before using it.
  • Evaluate and transform column data types.
  • Apply data shape transformations to table structures.
  • Combine queries.
  • Apply user-friendly naming conventions to columns and queries.
  • Edit M code in the Advanced Editor.

Module 5 :Design a semantic model in Power BI

  • Create common date tables
  • Configure many-to-many relationships
  • Resolve circular relationships
  • Design star schemas

Module 6 : Add measures to Power BI Desktop models

  • Determine when to use implicit and explicit measures.
  • Create simple measures.
  • Create compound measures.
  • Create quick measures.
  • Describe similarities of, and differences between, a calculated column and a measure.

Module 7 : Add calculated tables and columns to Power BI Desktop models

  • Create calculated tables.
  • Create calculated columns.
  • Identify row context.
  • Determine when to use a calculated column in place of a Power Query custom column.
  • Add a date table to your model by using DAX calculations.

Module 8 : Use DAX time intelligence functions in Power BI Desktop models

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

Module 9 : Optimize a model for performance in Power BI

  • Review the performance of measures, relationships, and visuals.
  • Use variables to improve performance and troubleshooting.
  • Improve performance by reducing cardinality levels.
  • Optimize DirectQuery models with table level storage.
  • Create and manage aggregations.

Module 10 : Design Power BI reports

  • Learn about the structure of a Power BI report.
  • Learn about report objects.
  • Select the appropriate visual type to use.

Module 11 : Configure Power BI report filters

  • Design reports for filtering.
  • Design reports with slicers.
  • Design reports by using advanced filtering techniques.
  • Apply consumption-time filtering.
  • Select appropriate report filtering techniques.

Module 12 : Enhance Power BI report designs for the user experience

  • Design reports to show details.
  • Design reports to highlight values.
  • Design reports that behave like apps.
  • Work with bookmarks.
  • Design reports for navigation.
  • Work with visual headers.
  • Design reports with built-in assistance.
  • Use specialized visuals.

Module 13 : Perform analytics in Power BI

  • Explore statistical summary.
  • Identify outliers with Power BI visuals.
  • Group and bin data for analysis.
  • Apply clustering techniques.
  • Conduct time series analysis.
  • Use the Analyze feature.
  • Use advanced analytics custom visuals.
  • Review Quick insights.
  • Apply AI Insights.

Module 14 : Create and manage workspaces in Power BI

  • Create and manage Power BI workspaces and items.
  • Distribute a report or dashboard.
  • Monitor usage and performance.
  • Recommend a development lifecycle strategy.
  • Troubleshoot data by viewing its lineage.
  • Configure data protection.

Module 15 : Manage semantic models in Power BI

  • Use a Power BI gateway to connect to on-premises data sources.
  • Configure a scheduled refresh for a semantic model .
  • Configure incremental refresh settings.
  • Manage and promote semantic models.
  • Troubleshoot service connectivity.
  • Boost performance with query caching (Premium).

Module 16 : Create dashboards in Power BI

  • Set a mobile view.
  • Add a theme to the visuals in your dashboard.
  • Configure data classification.
  • Add real-time dataset visuals to your dashboards.
  • Pin a live report page to a dashboard.

Module 17 : Implement row-level security

  • Configure row-level security by using a static method.
  • Configure row-level security by using a dynamic method.
LABS

Lab : Preparing Data in Power BI Desktop

  • Prepare Data

Lab : Loading Data in Power BI Desktop

  • Loading Data

Lab : Data Modeling in Power BI Desktop

  • Create Model Relationships
  • Configure Tables and column properties
  • Create hierarchies

Lab : Introduction to DAX in Power BI Desktop

  • Create calculated tables
  • Create calculated columns
  • Create measures

Lab : Advanced DAX in Power BI Desktop

  • Use the CALCULATE() function to manipulate filter context
  • Use Time Intelligence functions

Lab : Enhancing reports with interaction and formatting in Power BI Desktop

  • Create and configure Sync Slicers
  • Create a drillthrough page
  • Apply conditional formatting
  • Create and use Bookmarks

Lab : Designing a report in Power BI Desktop

  • Design a report
  • Configure visual fields and format properties

Lab : Creating a Dashboard in Power BI Service

  • Create a Dashboard
  • Pin visuals to a Dashboard
  • Use Q&A to create a dashboard tile

Lab : Data Analysis in Power BI Desktop

  • Create animated scatter charts
  • Use the visual to forecast values

Lab : Enforce Row-Level Security

  • Configure many-to-many relationships
  • Enforce row-level security

Lab : Preparing Data in Power BI Desktop

  • Prepare Data

Lab : Loading Data in Power BI Desktop

  • Loading Data

Lab : Data Modeling in Power BI Desktop

  • Create Model Relationships
  • Configure Tables and column properties
  • Create hierarchies

Lab : Introduction to DAX in Power BI Desktop

  • Create calculated tables
  • Create calculated columns
  • Create measures

Lab : Advanced DAX in Power BI Desktop

  • Use the CALCULATE() function to manipulate filter context
  • Use Time Intelligence functions

Lab : Enhancing reports with interaction and formatting in Power BI Desktop

  • Create and configure Sync Slicers
  • Create a drillthrough page
  • Apply conditional formatting
  • Create and use Bookmarks

Lab : Designing a report in Power BI Desktop

  • Design a report
  • Configure visual fields and format properties

Lab : Creating a Dashboard in Power BI Service

  • Create a Dashboard
  • Pin visuals to a Dashboard
  • Use Q&A to create a dashboard tile

Lab : Data Analysis in Power BI Desktop

  • Create animated scatter charts
  • Use the visual to forecast values

Lab : Enforce Row-Level Security

  • Configure many-to-many relationships
  • Enforce row-level security
WHO SHOULD ATTEND

The audience for this course are data professionals and business intelligence professionals who want to learn how to accurately perform data analysis using Power BI. This course is also targeted toward those individuals who develop reports that visualize data from the data platform technologies that exist on both in the cloud and on-premises.

PREREQUISITES

Successful Data Analysts start this role with experience of working with data in the cloud.

Specifically:

  • Understanding core data concepts.
  • Knowledge of working with relational data in the cloud.
  • Knowledge of working with non-relational data in the cloud.
  • Knowledge of data analysis and visualization concepts.

You can gain the prerequisites and a better understanding of working with data in Azure by completing Microsoft Azure Data Fundamentals before taking this course.