Duration
Pl-300: Microsoft Power Bi Data Analyst
3 days
Course Overview
This course covers the various methods and best practices that are in line with business and technical requirements for modelling, visualizing, and analysing data with Power BI. 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
Target Audience
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.
Learning Outcomes
By the end of this program, participants will be able to:
- Ingest, clean, and transform data
- Model data for performance and scalability
- Design and create reports for data analysis
- Apply and perform advanced report analytics
- Manage and share report assets
- Create paginated reports in Power BI
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.
Outline ( update: Oct 2024)
Module 1: Discover data analysis
Would you like to explore the journey of a data analyst and learn how a data analyst tells a story with data? In this module, you will explore the different roles in data and learn the different tasks of a data analyst.
In this module, you will:
- Learn about the roles in data.
- Learn about the tasks of a data analyst.
Module 2: Get started building with Power BI
Learn what Power BI is, including its building blocks and how they work together.
In this module, you will:
- 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: Create interactive reports using Copilot for Power BI
Copilot for Power BI uses Generative AI to simplify data visualization and create reports, making Power BI more insightful and accessible.
By the end of this module, you'll understand requirements for your semantic model and also be able to use
Copilot for Power BI to:
- Design semantic model
- Create visuals and reports
- Create summaries
Module 4: Get data in Power BI
You'll learn how to retrieve data from a variety of data sources, including Microsoft Excel, relational databases, and NoSQL data stores. You'll also learn how to improve performance while retrieving data.
By the end of this module, you'll be able to:
- 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 5: Clean, transform, and load data in Power BI
Power Query has an incredible amount of features that are dedicated to helping you clean and prepare your data for analysis. You will learn how to simplify a complicated model, change data types, rename objects, and pivot data. You will also learn how to profile columns so that you know which columns have the valuable data that you’re seeking for deeper analytics.
By the end of this module, you’ll be able to:
- 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 6: Choose a Power BI model framework
Describe model frameworks, their benefits and limitations, and features to help optimize your Power BI data models.
By the end of this module, you’ll be able to:
- 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 an appropriate Power BI model framework.
Module 7: Describe Power BI Desktop models
In this module, you'll learn about the Power BI Desktop model structure, star schema design basics, analytics queries, and report visual configuration. This module provides a strong foundation on which you can learn to optimize model designs and add model calculations.
By the end of this module, you'll be able to:
- Describe the structure of a Power BI Desktop model.
- Explain star schema design basics.
- Define the term analytic query and its phases.
- Describe how fields can be used to configure a report visual, which then generates an analytic query.
Module 8: Design a semantic model in Power BI
The process of creating a complicated data model in Power BI is straightforward. If your data is coming in from more than one transactional system, before you know it, you can have dozens of tables that you have to work with. Building a great data model is about simplifying the disarray. A star schema is one way to simplify a data model, and you’ll learn about the terminology and implementation of them in this module. You will also learn about why choosing the correct data granularity is important for performance and usability of your Power BI reports. Finally, you’ll learn about improving performance with your Power BI data models.
In this module, you will:
- Create common date tables
- Configure many-to-many relationships
- Resolve circular relationships
- Design star schemas
Module 9: Write DAX formulas for Power BI Desktop models
In this module, you'll learn how to write DAX formulas to create calculated tables, calculated columns, and measures, which are different types of model calculations. Additionally, you'll learn how to write and format DAX formulas, which consist of expressions that use functions, operators, references to model objects, constants, and variables.
By the end of this module, you'll be able to:
- Describe the different DAX calculation types.
- Write DAX formulas.
- Describe DAX data types.
- Work with DAX functions.
- Use DAX operators.
- Use DAX variables.
Module 10: Add measures to Power BI Desktop models
In this module, you'll learn how to work with implicit and explicit measures. You'll start by creating simple measures, which summarize a single column or table. Then, you'll create more complex measures based on other measures in the model. Additionally, you'll learn about the similarities of, and differences between, a calculated column and a measure.
By the end of this module, you'll be able to:
- 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 11: Add calculated tables and columns to Power BI Desktop models
By the end of this module, you'll be able to add calculated tables and calculated columns to your semantic model. You'll also be able to describe row context, which is used to evaluated calculated column formulas. Because it's possible to add columns to a table using Power Query, you'll also learn when it's best to create calculated columns instead of Power Query custom columns.
By the end of this module, you'll be able to:
- 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 12 : Modify DAX filter context in Power BI Desktop models
By the end of this module, you'll be able to describe and work with filter context, which is used to evaluate measure formulas.
Learning objectives
By the end of this module, you'll be able to:
- Describe filter context.
- Use the CALCULATE function to modify filter context.
- Pass filters to the CALCULATE function.
- Pass filter modifiers to the CALCULATE function.
- Perform context transition.
Module 13: Use DAX time intelligence functions in Power BI Desktop models
By the end of this module, you'll learn the meaning of time intelligence and how to add time intelligence DAX calculations to your model.
By the end of this module, you'll be able to:
- Define time intelligence.
- Use common DAX time intelligence functions.
- Create useful intelligence calculations.
Module 14: Optimize a model for performance in Power BI
Performance optimization, also known as performance tuning, involves making changes to the current state of the semantic model so that it runs more efficiently. Essentially, when your semantic model is optimized, it performs better.
Learning objectives
By the end of this module, you will be able to:
- 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 15: Scope report design requirements
Gathering appropriate inputs to scope your report design requirements involves identifying your audience, determining the suitable report types, and defining their interface and experience requirements. This module provides you with a strong foundation on which to learn how to plan your report design requirements.
In this module, you will:
- Determine business goals.
- Identify your audience.
- Determine report types.
- Define user interface requirements.
- Define user experience requirements.
Module 16: Design Power BI reports
Because Power BI includes more than 30 core visuals, it can be challenging for a beginner to select the correct visual. This module will guide you through selecting the most appropriate visual type to meet your design and report layout requirements.
In this module, you will:
- Learn about the structure of a Power BI report.
- Learn about report objects.
- Select the appropriate visual type to use.
Module 17: Create visual calculations in Power BI Desktop
Calculations in Power BI are necessary to enrich data analysis. Visual calculations simplify complex formulas, enhance performance, and reduce maintenance.
By the end of this module, you'll be able to:
- Understand visual calculations and how they differ from measures.
- Create visual calculations in Power BI Desktop.
- Use parameters in visual calculations.
Module 18: Configure Power BI report filters
Report filtering is a complex topic because many techniques are available for filtering a Microsoft Power BI report. However, with complexity comes control, allowing you to design reports that meet requirements and expectations. Some filtering techniques apply at design time, while others are relevant at report consumption time (in reading view). What matters is that your report design allows report consumers to intuitively narrow down to the data points that interest them.
In this module, you will:
- 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 19: Enhance Power BI report designs for the user experience
The features and capabilities that are covered in this module will help you enhance your reports to make them more refined.
In this module, you will:
- 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 20: Perform analytics in Power BI
You'll learn how to use Power BI to perform data analytical functions, how to identify outliers in your data, how to group data together, and how to bin data for analysis. You'll also learn how to perform time series analysis. Finally, you'll work with advanced analytic features of Power BI, such as Quick Insights, AI Insights, and the Analyze feature.
In this module, you'll:
- 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 21: Create and manage workspaces in Power BI
Learn how to navigate the Power BI service, create and manage workspaces and related items, and distribute reports to users.
In this module, you will:
- 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 22: Manage semantic models in Power BI
With Microsoft Power BI, you can use a single semantic model to build many reports. Reduce your administrative overhead even more with scheduled semantic model refreshes and resolving connectivity errors.
In this module, you will:
- 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 23: Create dashboards in Power BI
Microsoft Power BI dashboards are different than Power BI reports. Dashboards allow report consumers to create a single artifact of directed data that is personalized just for them. Dashboards can be composed of pinned visuals that are taken from different reports. Where a Power BI report uses data from a single semantic model, a Power BI dashboard can contain visuals from different semantic models.
In this module, you'll:
- Set a mobile view.
- Add a theme to the visuals in your dashboard.
- Add real-time semantic model visuals to your dashboards.
- Pin a live report page to a dashboard.
Module 24: Implement row-level security
Row-level security (RLS) allows you to create a single or a set of reports that targets data for a specific user. In this module, you'll learn how to implement RLS by using either a static or dynamic method and how Microsoft Power BI simplifies testing RLS in Power BI Desktop and Power BI service.
In this module, you will:
- Configure row-level security by using a static method.
- Configure row-level security by using a dynamic method.
Agenda
TIME
DAY 3
09:00 - 10:30
MODULE 19 & 20
10:30 – 10:45
MORNING BREAK
10:45 – 12:30
MODULE 21 & 22
12:30 – 13:30
LUNCH BREAK
13:30 – 15:30
MODULE 23 & 24
15:30 – 15:45
AFTERNOON BREAK
15:45 – 17:00
MODULE 17 & 18
QNA & EXAM BRIEFING
END OF THE DAY
Programme scope, delivery arrangements and suitability are confirmed during enquiry.