Section 1 : Introduction
Lecture 1 The Power BI ecosystem 00:00:28 Duration
Lecture 2 What is Power BI 00:02:05 Duration
Lecture 3 Understanding ETL (extract, transform, and load) 00:01:56 Duration
Lecture 4 Focus on Power Query 00:02:17 Duration
Lecture 5 Course considerations 00:01:35 Duration

Section 2 : Extracting Data Files
Lecture 1 Connecting to CSV or text files 00:02:25 Duration
Lecture 2 Manually entering data 00:01:25 Duration
Lecture 3 Connecting to an Excel file 00:03:01 Duration
Lecture 4 Connecting to a PDF file 00:02:57 Duration
Lecture 5 Connecting to folders

Section 3 : Extracting Data Databases
Lecture 1 Connecting to databases 00:05:34 Duration
Lecture 2 Comparing data connection modes
Lecture 3 Query folding and native queries 00:03:19 Duration

Section 4 : Extracting Data Web and Other Options
Lecture 1 Connecting to web tables 00:06:15 Duration
Lecture 2 Querying API data 00:02:33 Duration
Lecture 3 Querying REST API connections 00:07:53 Duration
Lecture 4 Configuring OData feeds 00:01:54 Duration
Lecture 5 Installing Python 00:02:25 Duration
Lecture 6 Running Python scripts 00:02:02 Duration

Section 5 : Transforming Data Cleaning
Lecture 1 Leveraging metadata 00:01:28 Duration
Lecture 2 Leveraging data types 00:02:49 Duration
Lecture 3 Making initial field transformations 00:04:30 Duration
Lecture 4 Splitting fields 00:03:05 Duration
Lecture 5 Merging fields 00:01:56 Duration
Lecture 6 Cleaning text fields 00:02:07 Duration
Lecture 7 Transforming numerical fields 00:02:18 Duration
Lecture 8 Removing or replacing values 00:02:36 Duration
Lecture 9 Filtering and removing duplicates
Lecture 10 Accessing native query in cleaning 00:04:40 Duration

Section 6 : Transforming Data Integration
Lecture 1 Introducing table objects 00:04:06 Duration
Lecture 2 Introducing list and record objects 00:06:13 Duration
Lecture 3 Working with binary objects 00:03:35 Duration
Lecture 4 Grouping data 00:01:50 Duration
Lecture 5 Pivoting data 00:06:36 Duration
Lecture 6 Transposing data 00:02:10 Duration
Lecture 7 Unpivoting data 00:01:44 Duration
Lecture 8 Accessing native query in integration 00:04:23 Duration

Section 7 : Transforming Data Enrichment
Lecture 1 Leveraging text formulas 00:08:11 Duration
Lecture 2 Conditional formulas 00:02:51 Duration
Lecture 3 Filling up or down columns 00:01:43 Duration
Lecture 4 Leveraging date formulas 00:05:42 Duration
Lecture 5 Combining binary files with formulas 00:06:30 Duration
Lecture 6 Accessing native query in enrichment 00:03:25 Duration

Section 8 : Leveraging M Language Logic and Syntax
Lecture 1 Working with Query Editor steps 00:03:30 Duration
Lecture 2 Breaking down syntax 00:01:53 Duration
Lecture 3 Renaming steps in M 00:04:20 Duration
Lecture 4 Consolidating M steps 00:02:16 Duration
Lecture 5 Adding data types as custom M code 00:02:41 Duration
Lecture 6 Connecting to zipped binary data 00:02:59 Duration

Section 9 : Leveraging M Language Objects
Lecture 1 Utilizing parameters
Lecture 2 Creating list objects 00:04:02 Duration
Lecture 3 Referencing a list as a column in a table 00:03:00 Duration
Lecture 4 Leveraging record objects 00:01:49 Duration
Lecture 5 Leveraging list functions 00:01:57 Duration
Lecture 6 Creating date tables 00:03:03 Duration
Lecture 7 Looping with lists 00:06:34 Duration
Lecture 8 Combining list objects 00:05:36 Duration

Section 10 : Leveraging M language Custom Functions
Lecture 1 Setting up custom functions 00:06:23 Duration
Lecture 2 Converting queries into functions
Lecture 3 Configuring custom filtering 00:05:23 Duration

Section 11 : Loading Data
Lecture 1 Configuring loading options 00:03:05 Duration
Lecture 2 Fixing errors 00:03:24 Duration
Lecture 3 Refreshing data 00:06:29 Duration
Lecture 4 Joining sets of data 00:07:11 Duration
Lecture 5 Composite models 00:02:19 Duration