16 hours

Course Description

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.

Learning Outcomes:

Upon completing this course, participants will be able to:

1. Understand the role of Data Analysts in the data space and the Microsoft Data Analytics ecosystem.
2. Utilize Power BI to retrieve data from various sources and optimize data connectivity and storage.
3. Clean, transform, and load data in Power BI, including data shaping, enhancing data structures, and performing data profiling.
4. Design and develop effective data models in Power BI, considering performance, scalability, and addressing common data modeling challenges.
5. Create model calculations using DAX (Data Analysis Expressions) to enhance data analysis and solve calculation problems.
6. Optimize data models for performance, including techniques for optimizing performance in DirectQuery models.
7. Design and build reports in Power BI, selecting appropriate visuals, creating page layouts, and applying essential functionality.
8. Create compelling dashboards in Power BI, utilizing navigation tools, enhancing usability, and delivering insights effectively.
9. Manage files and datasets in Power BI, including utilizing parameters, managing datasets, building dynamic reports, and configuring dataset refresh options.

By mastering these learning outcomes, participants will acquire the necessary skills to effectively utilize Power BI for data analytics and reporting, enabling them to make informed business decisions based on valuable insights.

Prerequisites

• 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.

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