Microsoft Power BI Data Analyst (PL-300)

Course Overview

 

1 - Discover data analysis

• Overview of data analysis
• Roles in data
• Tasks of a data analyst

2 - Get started building with Power BI

• Use Power BI
• Building blocks of Power BI
• Tour and use the Power BI service

3 - Get data in Power BI

• Get data from files
• Get data from relational data sources
• Create dynamic reports with parameters
• Get data from a NoSQL database
• Get data from online services
• Select a storage mode
• Get data from Azure Analysis Services
• Fix performance issues
• Resolve data import errors

4 - Clean, transform, and load data in Power BI

• Shape the initial data
• Simplify the data structure
• Evaluate and change column data types
• Combine multiple tables into a single table
• Profile data in Power BI
• Use Advanced Editor to modify M code

5 - Describe Power BI Desktop models

• Star schema design
• Analytic queries
• Configure report visuals

6 - 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

7 - Design a semantic model in Power BI

• Work with tables
• Create a date table
• Work with dimensions
• Define data granularity
• Work with relationships and cardinality
• Resolve modeling challenges

8 - Write DAX formulas for Power BI Desktop models

• Write DAX formulas
• DAX data types
• Work with DAX functions
• Use DAX operators
• Use DAX variables

9 - Add measures to Power BI Desktop models

• Create simple measures
• Create compound measures
• Create quick measures
• Compare calculated columns with measures

10 - Add calculated tables and columns to Power BI Desktop models

• Create calculated columns
• Learn about row context
• Choose a technique to add a column

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

• Use DAX time intelligence functions
• Additional time intelligence calculations

12 - Optimize a model for performance in Power BI

• Review performance of measures, relationships, and visuals
• Use variables to improve performance and troubleshooting
• Reduce cardinality
• Optimize DirectQuery models with table level storage
• Create and manage aggregations

13 - Enforce Power BI model security

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

14 - Scope report design requirements

• Identify the audience
• Determine report types
• Define user interface requirements
• Define user experience requirements
• Explore report designs

15 - Design Power BI reports

• Design the analytical report layout
• Design visually appealing reports
• Report objects
• Select report visuals
• Select report visuals to suit the report layout
• Format and configure visualizations
• Work with key performance indicators

16 - Configure Power BI report filters

• Apply filters to the report structure
• Apply filters with slicers
• Design reports with advanced filtering techniques
• Consumption-time filtering
• Select report filter techniques
• Case study - Configure report filters based on feedback

17 - 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
• Tune report performance
• Optimize reports for mobile use

18 - 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
• Create what-if parameters
• Use specialized visuals

19 - Create paginated reports

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

20 - Create and manage workspaces in Power BI

• Distribute a report or dashboard
• Monitor usage and performance
• Recommend a development life cycle strategy
• Troubleshoot data by viewing its lineage
• Configure data protection

21 - Manage semantic models in Power BI

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

22 - Create dashboards in Power BI

• Configure data alerts
• Explore data by asking questions
• Review Quick insights
• Add a dashboard theme
• Pin a live report page to a dashboard
• Configure a real-time dashboard
• Set mobile view

23 - Implement row-level security

• Configure row-level security with the static method
• Configure row-level security with the dynamic method

Prerequisites

• 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.

Microsoft Azure Data Fundamentals is recommended (KT-DP-900T00)