BPB E Learning

Creating our initial project file

Working with the attached project files

Connecting to our data source_new

Editing and removing rows

Changing data types

Transforming Data - Query Editor

Replace Values

Close _ Apply

Connecting Power BI to a csv file

Connecting to a Web Page

Extract Characters

Splitting _ Merging Columns

Create a conditional column

Columns from examples

Merging Queries

Pivoting _ Unpivoting

Appending Tables

Practise _ Solution PopulationTable

Fact Dimension Model

Practise Load Dimension Table

Organizing our Queries in Groups

Entering data manually

Creating an index column

Workflow _ more transformations

Module Summary

Excersice 1 - Instructions

Exercise solution

Advanced Editor - Best practise

References vs. Duplicates

Enable Disable Load _ Report Refresh

Group by

Mathematical Operations

Run R Script

Using Parameters to dynamically transform data

M-language Basics

M-Language Values, Lists _ Tables

M-Language Functions

M-Language More functions _ steps

Exercise 2 - Instructions

Exercise 2 - solution

Understanding relationships

Create _ Edit relationships

One-to-Many and One-to-One Relationship

Cross filter direction

ActivateDeactivate Relationships

Create Model Summary

Exersice 3 - Solution

Exercise 3 - Create Model

Our first visual

The format tab

Tables

Conditional Formatting

The pie chart

All about the Filter visual

Filter pane for developers

Cross filtering _ Edit interactions

Exercise 4 - Instructions

Exercise 4 - Solution

Syncing slicers across pages

Drill down

Drill through

Tree map visual

Decomposition tree

Matrix visual

Edit pages

Buttons _ Actions

Bookmarks to customize your report

Analytics and Forecast with Line Charts

Working with Custom Visuals

Get data using R _ R Script Visual (script in nächster Lektion)

Asking Questions - Q _ A Visual

Wrap up Data Visualization

Python intro (Plan of attack)

Setting up Python

Transforming data using Python scripts

Creating visualizations using Python

Python visual

Python visual _ Violine plots, ridge plots _ correlation analysis plots

_ Violine plots, ridge plots _ correlation analysis plots

Text Analysis using Python

Performance _ Troubleshooting

Module intro - Best Practises

Best practise #1 - Show Empathy _ Identify the requirements

Best practise # 2 - Finding the most suitable KPIs

Best Practise #3 - Choose an effective visualization

Best Practise #4 Make use of natural reading pattern

Best practise # 5 - Tell a story using visual cues

Best practise # 6 - Avoid Chaos _ Group information

Wrap up - Stroytelling with data

FullDatesTable (script to be used in your future projects)

Welcome to DAX

Let_s look at our data

Measures vs. Calculated Columns

CALENDARAUTO

CALENDAR

How to create a complete date table

Key Measures Table

Aggregation functions

COUNT, COUNTA

SUMX - How does it work

CALCULATE Basics

FILTER

ALL

ALLSELECTED

ALLEXCEPT

Quickmeasures - How to use them in a smart way

DAX - Analytics

How do we go on now

Power BI Pro vs. Premium _ Registration (+Text nach der Lektion mit Alternative)

Discovering the workspaces

Connecting Power BI Desktop _ Cloud

Understanding Datasets _ Reports

Working with the reports

Updating the reports from Power BI Desktop

Creating and working with Workspaces

Installing _ Using a Data Gateway

Get Quick Insights

Creating Dashboards

Sharing our results through Apps

Power BI Mobile App

Creating the layout for the Mobile App

Cloud Wrap up

RLS - EN - Intro

RLS - Creating RLS

RLS in the Cloud

RLS - Data Model

Dynamic RLS

RLS - Dynamic Many-to-Many

RLS - Hierarchical RLS

JSON _ REST API

Connecting to a SQL database

Cloud Wrap up

Installing _ Using a Data Gateway

Get Quick Insights

Creating Dashboards

Sharing our results through Apps

Power BI Mobile App

Creating the layout for the Mobile App

Congratulations _ Next steps

The End