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PL-300T00 - Microsoft Power BI Data Analyst

Duration: 3.0 days

This course covers 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 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.

  • Learn about the roles in data.
  • Learn about the tasks of a data analyst.
  • 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.
  • 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
  • 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.
  • Create common date tables
  • Configure many-to-many relationships
  • Resolve circular relationships
  • Design star schemas
  • Build quick measures.
  • Create calculated columns.
  • Use DAX to build measures.
  • Discover how context affects DAX measures.
  • Use the CALCULATE function to manipulate filters.
  • Implement time intelligence by using DAX.
  • 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.
  • Add visualization items to reports.
  • Choose an effective visualization.
  • Format and configure visualizations.
  • Import a custom visual.
  • Add an R or Python visual.
  • Design a report layout.
  • Add buttons, bookmarks, and selections.
  • Design report navigation.
  • Use basic interactions.
  • Use advanced interactions and drillthrough.
  • Configure conditional formatting.
  • Apply slicing, filtering, and sorting.
  • Publish and export reports.
  • Comment on reports.
  • Use Performance analyzer to tune reports.
  • Optimize reports for mobile use.
  • 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.
  • 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.
  • Use the Q&A visual.
  • Find important factors with the Key influencers visual.
  • Use the Decomposition Tree visual to break down a measure.
  • Distribute a report or dashboard.
  • Monitor usage and performance.
  • Recommend a development life cycle strategy.
  • Troubleshoot data by viewing its lineage.
  • Configure data protection.
  • Create dynamic reports with parameters.
  • Create what-if parameters.
  • Use a Power BI gateway to connect to on-premises data sources.
  • Configure a scheduled refresh for a dataset.
  • Configure incremental refresh settings.
  • Manage and promote datasets.
  • Troubleshoot service connectivity.
  • Boost performance with query caching (Premium).
  • Configure row-level security by using a static method.
  • Configure row-level security by using a dynamic method.

1. Get started with Microsoft data analytics

Businesses need data analysis more than ever. In this learning path, you will learn about the life and journey of a data analyst, the skills, tasks, and processes they go through in order to tell a story with data so trusted business decisions can be made. You will learn how the suite of Power BI tools and services are used by a data analyst to tell a compelling story through reports and dashboards, and the need for true BI in the enterprise.

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2. Prepare data for analysis with Power BI

You'll learn how to use Power Query to extract data from different data sources, choose a storage mode, and connectivity type. You'll also learn to profile, clean, and load data into Power BI before you model your data.

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3. Model data with Power BI

Learn what a Power BI semantic model is, which data loading approach to use, and how to build out your semantic model to get the insights you need.

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4. Build Power BI visuals and reports

Turn data into interactive, actionable insights with Power BI Desktop visuals and reports.

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5. Manage workspaces and datasets in Power BI

In this Learning Path, you'll learn how to publish Power BI reports to the Power BI service. You'll also learn how to create workspaces, manage related items, and data refreshes for up-to-date reports. Additionally, implement row-level security to restrict user access to relevant data without the need for multiple reports.

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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.

N/A

Skills measured

  • Prepare the data
  • Model the data
  • Visualize and analyze the data
  • Deploy and maintain assets

Scheduled DateLocationFeesRegister
12 Aug 2024 - 14 Aug 2024 Singapore SGD 2100
12 Aug 2024 - 14 Aug 2024 Virtual ILT SGD 2100
16 Sep 2024 - 18 Sep 2024 Virtual ILT SGD 2100
16 Sep 2024 - 18 Sep 2024 Singapore SGD 2100
14 Oct 2024 - 16 Oct 2024 Singapore SGD 2100
14 Oct 2024 - 16 Oct 2024 Virtual ILT SGD 2100
11 Nov 2024 - 13 Nov 2024 Virtual ILT SGD 2100
11 Nov 2024 - 13 Nov 2024 Singapore SGD 2100
16 Dec 2024 - 18 Dec 2024 Singapore SGD 2100
16 Dec 2024 - 18 Dec 2024 Virtual ILT SGD 2100



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