Develop dynamic reports with Microsoft Power BI

kurz

Základní info

Transform and load data, define semantic model relationships and calculations, create interactive visuals, and distribute reports using Power BI.

Prerequisites

Completion of the Get started with Microsoft data analytics is recommended.

Modules in this learning path

Get data in Power BI

You'll learn how to retrieve data from a variety of data sources, including Microsoft Excel, relational databases, and NoSQL data stores. You'll also learn how to improve performance while retrieving data.

Introduction
Get data from files
Get data from relational data sources
Create dynamic reports with parameters
Get data from a NoSQL database
Get data from online services
Select a storage mode
Get data from Azure Analysis Services
Fix performance issues
Resolve data import errors
Exercise - Prepare data in Power BI Desktop
Check your knowledge
Summary

Clean, transform, and load data in Power BI

Power Query has an incredible number of features that are dedicated to helping you clean and prepare your data for analysis. You'll learn how to simplify a complicated model, change data types, rename objects, and pivot data. You'll also learn how to profile columns so that you know which columns have the valuable data that you’re seeking for deeper analytics.

Introduction
Shape the initial data
Simplify the data structure
Evaluate and change column data types
Combine multiple tables into a single table
Profile data in Power BI
Use Advanced Editor to modify M code
Exercise - Load data in Power BI Desktop
Check your knowledge
Summary

Design a semantic model in Power BI

The process of creating a complicated semantic model in Power BI is straightforward. If your data is coming in from more than one transactional system, before you know it, you can have dozens of tables that you have to work with. Building a great semantic model is about simplifying the disarray. A star schema is one way to simplify a semantic model, and you learn about the terminology and implementation of them in this module. You will also learn about why choosing the correct data granularity is important for performance and usability of your Power BI reports. Finally, you learn about improving performance with your Power BI semantic models.

Introduction
Work with tables
Create a date table
Work with dimensions
Define data granularity
Work with relationships and cardinality
Resolve modeling challenges
Exercise - Model data in Power BI Desktop
Check your knowledge
Summary

Add measures to Power BI Desktop models

In this module, you'll learn how to work with implicit and explicit measures. You'll start by creating simple measures, which summarize a single column or table. Then, you'll create more complex measures based on other measures in the model. Additionally, you'll learn about the similarities of, and differences between, a calculated column and a measure.

Introduction
Create simple measures
Create compound measures
Create quick measures
Compare calculated columns with measures
Check your knowledge
Exercise - Create DAX Calculations in Power BI Desktop
Summary

Add calculated tables and columns to Power BI Desktop models

By the end of this module, you'll be able to add calculated tables and calculated columns to your semantic model. You'll also be able to describe row context, which is used to evaluated calculated column formulas. Because it's possible to add columns to a table using Power Query, you'll also learn when it's best to create calculated columns instead of Power Query custom columns.

Introduction
Create calculated columns
Learn about row context
Choose a technique to add a column
Check your knowledge
Summary

Design Power BI reports

Because Power BI includes more than 30 core visuals, it can be challenging for a beginner to select the correct visual. This module will guide you through selecting the most appropriate visual type to meet your design and report layout requirements.

Introduction
Design the analytical report layout
Design visually appealing reports
Report objects
Select report visuals
Select report visuals to suit the report layout
Format and configure visualizations
Work with key performance indicators
Exercise - Design a report in Power BI desktop
Check your knowledge
Summary

Configure Power BI report filters

Report filtering is a complex topic because many techniques are available for filtering a Microsoft Power BI report. However, with complexity comes control, allowing you to design reports that meet requirements and expectations. Some filtering techniques apply at design time, while others are relevant at report consumption time (in reading view). What matters is that your report design allows report consumers to intuitively narrow down to the data points that interest them.

Introduction to designing reports for filtering
Apply filters to the report structure
Apply filters with slicers
Design reports with advanced filtering techniques
Consumption-time filtering
Select report filter techniques
Case study - Configure report filters based on feedback
Check your knowledge
Summary

Create and manage workspaces in Power BI

Learn how to navigate the Power BI service, create and manage workspaces and related items, and distribute reports to users.

Introduction
Distribute a report or dashboard
Monitor usage and performance
Recommend a development life cycle strategy
Troubleshoot data by viewing its lineage
Configure data protection
Check your knowledge
Summary

Manage semantic models in Power BI

With Microsoft Power BI, you can use a single semantic model to build many reports. Reduce your administrative overhead even more with scheduled semantic model refreshes and resolving connectivity errors.

Introduction
Use a Power BI gateway to connect to on-premises data sources
Configure a semantic model scheduled refresh
Configure incremental refresh settings
Manage and promote semantic models
Troubleshoot service connectivity
Boost performance with query caching (Premium)
Check your knowledge
Summary

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