Visão Geral

Este Curso Pwer BI PL-300T00 Microsoft Power BI Data Analyst abrange os vários métodos e melhores práticas alinhados aos requisitos técnicos e de negócios de modelagem, visualização e análise de dados do Power BI. Também mostra como acessar e processar dados de uma variedade de fontes de dados, como fontes relacionais e não relacionais. Por fim, o curso também discute como gerenciar e implantar relatórios e painéis para o compartilhamento e a distribuição de conteúdo.

O curso PL-300T00: Microsoft Power BI Data Analyst equipa profissionais com as habilidades para analisar dados e criar relatórios interativos usando o Power BI. Os participantes aprenderão como se conectar a fontes de dados, transformar dados e construir modelos de dados usando DAX. O curso também abrange a criação de visuais eficazes, a implementação de segurança em nível de linha e a otimização do desempenho de relatórios e painéis. Este Curso Pwer BI PL-300T00 Microsoft Power BI Data Analyst é ideal para aqueles que buscam o treinamento Power BI PL-300, que oferece uma compreensão abrangente do Power BI para inteligência de negócios e tomada de decisão baseada em dados.

Objetivo

Após realizar este Curso Pwer BI PL-300T00 Microsoft Power BI Data Analyst, você será capaz de:

• Ingerir, limpar e transformar dados
• Dados do modelo para desempenho e escalabilidade
• Projetar e criar relatórios para análise de dados
• Aplique e execute análises avançadas de relatórios
• Gerenciar e compartilhar ativos de relatórios
• Crie relatórios paginados no Power BI
• Coletar e transformar dados de múltiplas fontes.
• Modelar dados para análise avançada.
• Criar visualizações de dados interativas e impactantes.
• Utilizar DAX (Data Analysis Expressions) para cálculos avançados.
• Publicar e compartilhar relatórios no Power BI Service.
• Preparar-se para a certificação Microsoft PL-300: Power BI Data Analyst.

Publico Alvo

Este Curso Pwer BI PL-300T00 Microsoft Power BI Data Analyst foi desenvolvido para profissionais de dados e de Business Intelligence que desejam aprender como executar com precisão a análise de dados usando o Power BI. Este curso também é direcionado àqueles indivíduos que desenvolvem relatórios para visualização de dados das tecnologias da plataforma de dados existentes na nuvem e no local.

Pre-Requisitos

• Conhecimento de conceitos de análise e visualização de dados
• Conhecimento de trabalho com dados não relacionais na nuvem
• Conhecimento de trabalho com dados relacionais na nuvem
• Compreendendo os principais conceitos de dados

Materiais

Conteúdo Programatico

Get started with Microsoft data analytics

1. Discover data analysis
   1. Learn about the roles in data.
   2. Learn about the tasks of a data analyst.
2. Get started building with Power BI
   1. How Power BI services and applications work together.
   2. Explore how Power BI can make your business more efficient.
   3. How to create compelling visuals and reports.
3. Create interactive reports using Copilot for Power BI
   1. Design semantic model
   2. Create visuals and reports
   3. Create summaries

Prepare data for analysis with Power BI

1. Get data in Power BI
   1. Identify and connect to a data source
   2. Get data from a relational database, like Microsoft SQL Server
   3. Get data from a file, like Microsoft Excel
   4. Get data from applications
   5. Get data from Azure Analysis Services
   6. Select a storage mode
   7. Fix performance issues
   8. Resolve data import errors
2. Clean, transform, and load data in Power BI
   1. Resolve inconsistencies, unexpected or null values, and data quality issues.
   2. Apply user-friendly value replacements.
   3. Profile data so you can learn more about a specific column before using it.
   4. Evaluate and transform column data types.
   5. Apply data shape transformations to table structures.
   6. Combine queries.
   7. Apply user-friendly naming conventions to columns and queries.
   8. Edit M code in the Advanced Editor.

Model data with Power BI

1. Describe Power BI Desktop models
   1. Describe the structure of a Power BI Desktop model.
   2. Explain star schema design basics.
   3. Define the term analytic query and its phases.
   4. Describe how fields can be used to configure a report visual, which then generates an analytic query.
2. Choose a Power BI model framework
   1. Describe Power BI model fundamentals.
   2. Determine when to develop an import model.
   3. Determine when to develop a DirectQuery model.
   4. Determine when to develop a composite model.
   5. Choose an appropriate Power BI model framework.
3. Design a semantic model in Power BI
   1. Create common date tables
   2. Configure many-to-many relationships
   3. Resolve circular relationships
   4. Design star schemas

• Write DAX formulas for Power BI Desktop models
  1. Describe the different DAX calculation types.
  2. Write DAX formulas.
  3. Describe DAX data types.
  4. Work with DAX functions.
  5. Use DAX operators.
  6. Use DAX variables.

1. Add measures to Power BI Desktop models
   1. Determine when to use implicit and explicit measures.
   2. Create simple measures.
   3. Create compound measures.
   4. Create quick measures.
   5. Describe similarities of, and differences between, a calculated column and a measure.
2. Add calculated tables and columns to Power BI Desktop models
   1. Create calculated tables.
   2. Create calculated columns.
   3. Identify row context.
   4. Determine when to use a calculated column in place of a Power Query custom column.
   5. Add a date table to your model by using DAX calculations.
3. Use DAX time intelligence functions in Power BI Desktop models
   1. Define time intelligence.
   2. Use common DAX time intelligence functions.
   3. Create useful intelligence calculations.
4. Optimize a model for performance in Power BI
   1. Review the performance of measures, relationships, and visuals.
   2. Use variables to improve performance and troubleshooting.
   3. Improve performance by reducing cardinality levels.
   4. Optimize DirectQuery models with table level storage.
   5. Create and manage aggregations.
5. Enforce Power BI model security
   1. Restrict access to Power BI model data with RLS.
   2. Restrict access to Power BI model objects with OLS.
   3. Apply good development practices to enforce Power BI model security.

Build Power BI visuals and reports

1. Scope report design requirements
   1. Determine business goals.
   2. Identify your audience.
   3. Determine report types.
   4. Define user interface requirements.
   5. Define user experience requirements.
2. Design Power BI reports
   1. Learn about the structure of a Power BI report.
   2. Learn about report objects.
   3. Select the appropriate visual type to use.
3. Create visual calculations in Power BI Desktop
   1. Understand visual calculations and how they differ from measures.
   2. Create visual calculations in Power BI Desktop.
   3. Use parameters in visual calculations.
4. Configure Power BI report filters
   1. Design reports for filtering.
   2. Design reports with slicers.
   3. Design reports by using advanced filtering techniques.
   4. Apply consumption-time filtering.
   5. Select appropriate report filtering techniques.
5. Enhance Power BI report designs for the user experience
   1. Design reports to show details.
   2. Design reports to highlight values.
   3. Design reports that behave like apps.
   4. Work with bookmarks.
   5. Design reports for navigation.
   6. Work with visual headers.
   7. Design reports with built-in assistance.
   8. Use specialized visuals.
6. Perform analytics in Power BI
   1. Explore statistical summary.
   2. Identify outliers with Power BI visuals.
   3. Group and bin data for analysis.
   4. Apply clustering techniques.
   5. Conduct time series analysis.
   6. Use the Analyze feature.
   7. Use advanced analytics custom visuals.
   8. Review Quick insights.
   9. Apply AI Insights.
7. Create paginated reports
   1. Get data.
   2. Create a paginated report.
   3. Work with charts and tables on the report.
   4. Publish the report.

Manage workspaces and datasets in Power BI

1. Create and manage workspaces in Power BI
   1. Create and manage Power BI workspaces and items.
   2. Distribute a report or dashboard.
   3. Monitor usage and performance.
   4. Recommend a development lifecycle strategy.
   5. Troubleshoot data by viewing its lineage.
   6. Configure data protection.
2. Manage semantic models in Power BI
   1. Use a Power BI gateway to connect to on-premises data sources.
   2. Configure a scheduled refresh for a semantic model.
   3. Configure incremental refresh settings.
   4. Manage and promote semantic models.
   5. Troubleshoot service connectivity.
   6. Boost performance with query caching (Premium).
3. Create dashboards in Power BI
   1. Set a mobile view.
   2. Add a theme to the visuals in your dashboard.
   3. Add real-time semantic model visuals to your dashboards.
   4. Pin a live report page to a dashboard.
4. Implement row-level security
   1. Configure row-level security by using a static method.
   2. Configure row-level security by using a dynamic method.