PL-300: Design and manage analytics solutions using Power BI
Length: 3 Day(s) Cost:$2995 + GST
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| Hamilton | ||||
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| Virtual Class |
This course will discuss the various methods and best practices that are in line with business and technical requirements for modeling, visualizing, and analyzing data with Power BI. The course will also show how to access and process data from a range of data sources including both relational and non-relational data. This course will also explore how to implement proper security standards and policies across the Power BI spectrum including datasets and groups. The course will also discuss how to manage and deploy reports and dashboards for sharing and content distribution.
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.
Successful Data Analysts start this course 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.
After completing this course, students 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
Get started with Microsoft data analytics
- Discover data analysis
- Learn about the roles in data.
- Learn about the tasks of a data analyst.
- Get started building with Power BI
- How Power BI services and applications work together.
- Explore how Power BI can make your business more efficient.
- How to create compelling visuals and reports.
- Create interactive reports using Copilot for Power BI
- Design semantic model
- Create visuals and reports
- Create summaries
Prepare data for analysis with Power BI
- 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
- 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.
Model data with Power BI
- Describe Power BI Desktop models
- 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.
- 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 an appropriate Power BI model framework.
- Design a semantic model in Power BI
- Create common date tables
- Configure many-to-many relationships
- Resolve circular relationships
- Design star schemas
- Write DAX formulas for Power BI Desktop models
- Describe the different DAX calculation types.
- Write DAX formulas.
- Describe DAX data types.
- Work with DAX functions.
- Use DAX operators.
- Use DAX variables.
- 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.
- 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.
- Use DAX time intelligence functions in Power BI Desktop models
- Define time intelligence.
- Use common DAX time intelligence functions.
- Create useful intelligence calculations.
- 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.
- Enforce Power BI model security
- Restrict access to Power BI model data with RLS.
- Restrict access to Power BI model objects with OLS.
- Apply good development practices to enforce Power BI model security.
Build Power BI visuals and reports
- Scope report design requirements
- Determine business goals.
- Identify your audience.
- Determine report types.
- Define user interface requirements.
- Define user experience requirements.
- Design Power BI reports
- Learn about the structure of a Power BI report.
- Learn about report objects.
- Select the appropriate visual type to use.
- Create visual calculations in Power BI Desktop
- Understand visual calculations and how they differ from measures.
- Create visual calculations in Power BI Desktop.
- Use parameters in visual calculations.
- 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.
- 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.
- 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.
- Create paginated reports
- Get data.
- Create a paginated report.
- Work with charts and tables on the report.
- Publish the report.
Manage workspaces and datasets in Power BI
- 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.
- 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).
- Create dashboards in Power BI
- 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.
- Implement row-level security
- Configure row-level security by using a static method.
- Configure row-level security by using a dynamic method.