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Microsoft Power BI Data Analyst (PL-300)

Virtual Learning: 1,350€ + IVA

REF: PL-300 Catálogo: Microsoft Área: Data & AI

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Duração:

3 dias

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Próxima Data:

Consulte-nos

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Local:

Online

Descrição

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.

*PVP por participante. A realização do curso nas datas apresentadas está sujeita a um quórum mínimo de inscrições.

Destinatários

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.

  • Área: Microsoft

  • Certificação Associada: PL-300

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Programa:

Module 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.

Lessons:

  • Discover data analysis
  • Get started building with Power BI
  • Create interactive reports using Copilot for Power BI

Module 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.

Lessons:

  • Get data in Power BI
  • Clean, transform, and load data in Power BI
  • Choose a Power BI model framework

Module 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.

Lessons:

  • Design a semantic model in Power BI
  • Write DAX formulas for Power BI Desktop models
  • Add measures to Power BI Desktop models
  • Add calculated tables and columns to Power BI Desktop models
  • Modify DAX filter context in Power BI Desktop models
  • Use DAX time intelligence functions in Power BI Desktop models
  • Optimize a model for performance in Power BI

Module 4: Build Power BI visuals and reports

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

Lessons:

  • Scope report design requirements
  • Design Power BI reports
  • Create visual calculations in Power BI Desktop
  • Configure Power BI report filters
  • Enhance Power BI report designs for the user experience
  • Perform analytics in Power BI

Module 5: Manage workspaces and semantic models 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.

Lessons:

  • Create and manage workspaces in Power BI
  • Manage semantic models in Power BI
  • Create dashboards in Power BI
  • Implement row-level security

Pré-requisitos:

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.

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