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DP-605 Develop dynamic reports with Microsoft Power BI

Duration:
Course Code: DP-605
Course Delivery: Virtual (1-Day) GMT/Virtual (1-Day) PST
Level: Intermediate

Course Overview

Microsoft Power BI offers a comprehensive solution for Data Analytics, from data ingestion to visualization and distribution. Through tools including Power BI Desktop, Power Query, and the Power BI service, users can create dynamic and interactive reports that provide valuable insights and inspire data-informed decisions within your organization. 
This course introduces the fundamental skills necessary for data analysis using Power BI.
 

Audience Profile

The ideal audience are those wanting to expand their knowledge of data modelling, visualization, and analysis with the use of Microsoft Power BI.

Course Objectives

After completing this course, students will be able to:

• Connect to data sources
• Transform and load data with Power Query Editor
• Extend semantic model with relationships and DAX
• Select visualizations and design report elements with Power BI Desktop
• Publish reports to Power BI service
• Deploy and maintain items in Power BI service

Prerequisites

Students for this course should be familiar with data manipulation and have some experience with data analysis.

Course Outline

Module 1: 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.

Lessons 

• 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

After completing this module, students will be able to:

• Identify and connect to a data source
• Get data from a relational database, such as Microsoft SQL Server
• Get data from a file, such as Microsoft Excel
• Get data from applications
• Get data from Azure Analysis Services
• Select a storage mode
• Fix performance issues
• Resolve data import errors

Module 2: 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.

Lessons

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

After completing this module, students will be able to:

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.

Module 3: +

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.

Lessons

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

After completing this module, students will be able to:

Create common date tables
Configure many-to-many relationships
Resolve circular relationships
Design star schemas

Module 4: 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.

Lessons

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

After completing this module, students will be able to:

Determine when to use implicit and explicit measures.
Create simple measures.
Create compound measures.
Create quick measures.
Describe similarities of, and differences between, a calculated column and a measure

 

Module 5: 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.

Lessons

• Introduction
• Create calculated columns
• Learn about row context
• Choose a technique to add a column

After completing this module, students will be able to:

• Create calculated tables.
• Create calculated columns.
• Identify row context.
• Determine when to use a calculated column in place of a Power Query custom column.
• Add a date table to your model by using DAX calculations.

Module 6: 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.

Lessons

• 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

After completing this module, students will be able to:

• Learn about the structure of a Power BI report.
• Learn about report objects.
• Select the appropriate visual type to use.

Module 7: 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.

Lessons

• 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

After completing this module, students will be able to:

• Design reports for filtering.
• Design reports with slicers.
• Design reports by using advanced filtering techniques.
• Apply consumption-time filtering.
• Select appropriate report filtering techniques.

Module 8: 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.

Lessons

• 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

After completing this module, students will be able to:

• Create and manage Power BI workspaces and items.
• Distribute a report or dashboard.
• Monitor usage and performance.
• Recommend a development lifecycle strategy.
• Troubleshoot data by viewing its lineage.
• Configure data protection.

Module 9: 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.

Lessons

• 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)

After completing this module, students will be able to:

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

 

Book this Course

Date Delivery Format Location Price Add to cart
31 May 2024 Virtual (1-Day) PST Online £195.00 £125.00 Book me in
14 June 2024 Virtual (1-Day) GMT Online £195.00 £125.00 Book me in
5 July 2024 Virtual (1-Day) PST Online £195.00 £125.00 Book me in
19 July 2024 Virtual (1-Day) GMT Online £195.00 £125.00 Book me in

If you have any questions or are looking for customised training for you or your team, please contact us

Exam Information