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. Finally, this course will show how to build paginated reports within the Power BI service and publish them to a workspace for inclusion within Power BI.

Course outline

Module 1: Introduction

This module explores the landscape of the Power BI portfolio and describes several use cases for Power BI. The course then identifies and describes the role and responsibilities of a Data analyst.

Lessons

The Power BI Portfolio

Identifying Tasks of the Data Analyst

Lab: Getting Started

Getting Started

After completing this module, students will be able to:

Describe the Power BI landscape of products and services.

Describe use cases for Power BI

Identify the tasks that are performed by a Data Analyst

Module 2: Getting and Profiling Data

This module explores identifying and connecting to different data sources. The student will also learn the basics of how to identify and optimize query performance issues. They will also learn how to perform proper data profiling in preparation for the subsequent step of cleaning and shaping the data prior to loading the data.

Lessons

Data Sources

Storage Modes

Query Performance

Data Profiling

Lab: Preparing Data in Power BI Desktop

Prepare Data

After completing this module, students will be able to:

Identify the different data sources

Explain the different connection methods and why

Identify query problems and optimize.

Identify data anomalies

Examine data structures

Module 3: Cleaning and Transforming Data

This module teaches the fundamental concepts of designing a data model for proper performance and scalability. It instills in the student a list of items to think about prior to building the model.

Lessons

User-Friendliness

Combining Queries

Data cleaning and transformation

Advanced capabilities

Configuring data loading and resolving errors

Lab: Loading Data in Power BI Desktop

Loading Data

After completing this module, students will be able to:

Resolve data inconsistencies

Apply data shape transformations

Evaluate and transform column data types

Resolve data import errors

Module 4: Designing a Data Model

This module teaches the fundamental concepts of designing a data model for proper performance and scalability. It instills in the student a list of items to think about prior to building the model.

Lessons

Data modeling basics

Measures and Dimensions

Model Performance

Lab: Data Modeling in Power BI Desktop

Create Model Relationships

Configure Tables

Review the model interface

Create Quick Measures

After completing this module, students will be able to:

Define relationships and their cardinality

Configure table and column properties

Define quick measures

Understand how the design of the model impacts performance

Module 5: Developing a Data Model

In this module, the student will apply the steps learned in the previous module and build a data model while learning and implementing additional items to create the foundation of the model. The student will be introduced to initial security concepts and the Q&A feature in this module.

Lessons

Common data modeling techniques

Adding columns to support the data model

Row-level security

Q&A considerations

Lab: Advanced Data Modeling

Create a many-to-many relationship

Enforce row-level security

After completing this module, students will be able to:

Resolve circular and many/many relationships

Create groupings and bindings

Describe, and set up, the Q&A feature

Module 6: Creating Model Calculations with DAX

This module first introduces the student to DAX and some of the critical functions and operators necessary to enhance a data model, including the concepts of Measures, calculated columns and tables, and Time Intelligence.

Lessons

Introduction to DAX

Creating tables and columns

Measures

The CALCULATE expression

Time-Intelligence functions

Lab: Using DAX in Power BI – Part 1

Create Calculated tables

Create Measures

Lab: Using DAX in Power BI – Part 2

Work with Filter content

Work with Time-Intelligence

Publish the Power BI Desktop file

After completing this module, students will be able to:

Use DAX for simple formulas and expressions

Create calculated tables and columns

Build simple measures

Module 7: Optimizing Model Performance

In this module, the student is introduced to steps, processes, and concepts necessary to optimize a data model for enterprise-level performance.

Lessons

Fine-tune the data model

Cardinality

Identifying performance issues

After completing this module, students will be able to:

Analyze query plans and dependencies

Identify poor performing measures and relationships

Work with aggregations

Improve cardinality levels

Module 8: Creating Reports

This module introduces the student to the fundamental concepts and principles of building a report, including selecting the correct visuals, designing a page layout, and applying basic but critical functionality including slicing and filtering. This important topic of designing for accessibility is also covered.

Lessons

Selecting a visualization

Configuring visualizations

Formatting pages

Enhancing the report

Lab: Designing a report in Power BI Desktop – Part 1

Create a report

After completing this module, students will be able to:

Design a page layout

Select and add the appropriate visualization type

Add basic report functionality

Understand and design for accessibility

Module 9: Enhancing Reports for Usability and Performance

This module helps the student think beyond the basics of report building and discusses topics for enhancing the report for usability and performance. The student will leave this module knowing that a report is not something to just look at, but is a living canvas that tells a story, and should be designed as such.

Lessons

Bookmarks and navigation

Designing cohesive pages and interactions

Improving reports

Lab: Designing a report in Power BI Desktop – Part 2

Configure Sync Slicers

Configure Drill-through

Add Conditional Formatting

Add Bookmarks and Buttons

Explore the Report

After completing this module, students will be able to:

Add Quick Insights

Configure Sync Slicers

Configure interactions between visuals

Identify usability enhancements

Module 10: Creating Dashboards

In this module, the student learns about dashboards and the many features and functionality they contain. The student learns how to take the report they built in the previous module and pin it to a dashboard, then enhance the dashboard for additional usability and insights.

Lessons

Dashboard design

Real-time dashboards

Dashboard enhancements

Lab: Creating a Power BI Dashboard

Create a Dashboard

Refresh the dataset

Review the dashboard

After completing this module, students will be able to:

Create a dashboard

Set up the Q&A feature

Mange tiles and work with lie report pages

Explain and set the mobile view

Module 11: Enhancing Reports and Applying Advanced Analytics

This module helps the student apply additional features to enhance the report for analytical insights into the data, equipping the student with the steps to use the report for actual data analysis. This module will also arm the student with additional steps and concepts to apply and perform advanced analytics on the report for even deeper and more meaningful data insights.

Lessons

Navigation

Basic analysis

Grouping, binning, and clustering

Analysis over time

Advanced analysis

Lab: Data Analysis in Power BI Desktop

Create a report

Create a Scatter chart

Create a Forecast

Work with a Decomposition Tree

Work with Key Influencers

After completing this module, students will be able to:

Explore statistical summary

Identify outliers in the data

Use the Q&A visual

Perform top N analysis

Module 12: Managing and Sharing Power BI Assets

In this module, the student will learn the concepts of managing Power BI assets, including datasets and workspaces, as well as how to apply role-level security to a dataset. This module teaches the student how to create and manage workspaces, as well as how to share content, including reports and dashboards, and how to distribute an App.

Lessons

Dataset management

Enhancing datasets

Configure row-level security

Create and manage workspaces

Enhancing datasets and reports in the workspace

Sharing and distributing content

Lab: Publishing and Sharing Power BI Content

Configure dataset security

Share a Dashboard

Publish an APP

After completing this module, students will be able to:

Configure dataset refresh

Configure row-level security on the dataset

Create and manage a workspace

Publish or update assets in a workspace

Understand workspace collaboration

Module 13: Working with Paginated Reports in Power BI

This module will teach the student about paginated reports. The student will learn what they are and how they fit into the Power BI spectrum, and then look at how to build and publish a report.

Lessons

Introduction to Paginated Reports

Data sources and datasets

Adding visual elements

Enhancing and publishing reports

Lab: Creating a Paginated report

Getting Started

Develop the report

After completing this module, students will be able to:

Explain paginated reports

Create a paginated report

Create and configure a data source and dataset.

Work with charts and tables on the report.

For Training Requirement Contact-

udithait@gmail.com

training@bluechiptraining.biz

Singapore-

+65 86738158

Microsoft Certified: Data Analyst Associate Training.