Power Query And M Language The Easy Way
Power Query And M Language The Easy Way
Last updated 3/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 10.43 GB | Duration: 20h 49m
Most complete and comprehensive course in Power Query and M Language with hands on exercises and demos step-by-step.
What you'll learn
Understand Power Query and its components
Understand power query to connect and explore your data
How to Explore reshape and enrich your data
How to create calculated columns
How to Shape or transform data to match your data analysis requirements
How to Refresh a query to import the latest data into a table
How to Combine data from multiple data sources
How to Filter a table based on size, value, or condition
How to Sort a table ranked by a criteria, such as the alphabetical or numerical value of one or multiple columns, and by ascending or descending order.
How to Group rows in a table
How to Expand/Extend a column
How to Aggregate data from a column by group operation, including Sum, Count, Average, Min, and Max
How to Insert a custom column into a table — Insert an Index or Custom column
How to Combine multiple queries by merging or appending them
There is no coding required! Power Query allows you to do that but it's not necessary
Build complex and custom transformation
Write M code to add/delete/transform custom columns
Implement Best practice in Power Query and M language
Explore how the M language can be used to write your own customized solutions
Use custom functions to extend and enhance Power Query
Create your own formulas and functions to go beyond simple data imports
Gain effiiciency by reducing the time it takes to prepare data for analysis, and make informed decisions more quickly
Gain productivity by properly preparing data yourself, rather than relying on others to do it
Requirements
Microsoft Power BI Desktop (free download)
This course is designed for PC/Windows users (currently not available for Mac)
Your willingness to learn and grow
This is a Power Query and M Language Training for beginners to advanced
Description
Companies are gathering more and more data everyday. Skills in data analysis, business intelligence / business analytics are highly in demand in today's job market. Microsoft Power BI is an advanced yet easy to use self service Business Intelligence / business analytics tool for that. It is same business intelligence. tools used by professional analysts and data scientists. Therefore they rely heavily on data. Data driven decision making is the key to success for any business in the world of tomorrow.Imagine how much power you when you know how to clean big data. Microsoft included power query and M language Engine virtually in every data product. You will be very surprised that you did not learn this earlier.One of the advantages of technology and having the skill is the opportunity it offers to scale your business and career. To be more productive, you need to work smarter. With low-code/no-code tools Microsoft Power Query and M Language, you can extract data from different sources, clean, reshape, remove, prepare, generate new data mashup, append and merge data .This is the most comprehensive and complete course in power query. We are going to cover over hundreds of data transformations in this course. We are covering Power Query in depth in this course does. Absolutely no experience required in Power Query or M Language. We will start from the basics and gradually build up your knowledge. I will introduce you to some great features of Power query and M Language with hands on demos. after completing this course you be able to transform you data like DBAs and ETL Developers.You do not have to learn R or python anymore. I am going to teach you to become data scientist just learn power query and M because you already know how to clean data. You can follow along with the provided learning material on your own computer at your own pace. I will basically hold your hand and teach you everything step-by-step.Understand Power Query and its componentsUnderstand power query to connect and explore your dataHow to explore, reshape and enrich your dataHow to create calculated columnsHow to shape or transform data to match your data analysis requirements.How to refresh a query to import the latest data into a tableHow to combine data from multiple data sourcesHow to filter a table based on size, value, or condition.How to sort a table ranked by a criteria, such as the alphabetical or numerical value of one or multiple columns, and by ascending or descending order.How to group rows in a tableHow to expand/extend a columnHow to aggregate data from a column by group operation, including sum, count, average, min, and max.How to Insert a custom column into a table — Insert an Index or custom columnHow to Combine multiple queries by merging or appending them.There is no coding required! Power Query allows you to do that but it's not necessary.Build complex and custom transformationWrite M code to add/delete/transform custom columnsImplement best practice in Power Query and M languageThis Course Also Comes With:Lifetime access to all future updatesFast & friendly support in the Q&A sectionCustom notes, homework exercises, checklists, templates, course quizzes to help get results fasterUdemy certificate of completion ready for downloadA 30 days "no questions asked" money back guarantee!Here is list of lectures :What are you going to learn in this courseThank you and how to get supportWhat is Power QueryWhy Microsoft created Power Query and why use itPower Query Interface ComponentsFirst things firstM Language Type Structures ValuesM Language Type Primitive ValuesM Language OperatorsWhat are Lists and how to create them using M LanguageWhat are Tables and RecordsCreate initial pbix fileData Source and Privacy SettingsUsing Parameters in Report-0Using Parameters in Report-1Using Parameters as File Path or Data SourceQuery OptionsManage Column using M LanguageReduce Rows using Power QueryReduce Rows using M LanguageSort Order for Data and Filters using Power QuerySort Order for Data using M LanguageSplit Column using Power QuerySplit Column using M LanguageGroup by or Grouping Data using Power Query-0Group by or Grouping Data using Power Query-1Group by using M LanguageData Type using Power Query and MHeaders as first row and First row as Headers using Power Query and MReplace Values using Power Query and MMerge Tables using Power Query-0Merge Tables using Power Query-1Append Tables using Power Query-0Append Tables using Power Query-1Group by or Grouping Data using Power Query-0Group by or Grouping Data using Power Query-1Headers as first row and First row as Headers using Power Query and MTranspose-Reverse-Count Rows using Power Query and MData Type and Rename using Power Query and MReplace - Fill using Power Query and MPivot - Unpivoting using Power QueryMove - Convert to List using Power QuerySplit Column using Power Query 0Split Column using Power Query 1Split Column using M LanguageFormat - Trim - clean -Lower - Upper Case using Power QueryFormat - Trim - clean -Lower - Upper Case using M LanguageMerge Columns using Power Query and M LanguageExtract using Power Query and M LanguageParse XML Data using Power Query and M LanguageParse JSON Data using Power Query and M LanguageStatistics using Power Query and M LanguageStandard and Scientific using Power Query and M LanguageTrigonometry - Rounding - Information using Power Query and M Language-0Trigonometry - Rounding - Information using Power Query and M Language-1Date Transformation using Power Query and M Language-0Date Transformation using Power Query and M Language-1Time-Duration Transformation using Power Query and M LanguageColumn From Example using Power Query and M LanguageCustom Column using Power Query and M Language-0Custom Column using Power Query and M Language-1Invoke Custom Column using Power Query and M Language-0Invoke Custom Column using Power Query and M Language-1Conditional Column using Power Query and M LanguageIndex Column using Power Query and M Language-0Index Column using Power Query and M Language-1Duplicate and Merge Column using Power Query and M LanguageFormat - Trim - clean -Lower - Upper Case using Power QueryFormat - Trim - clean -Lower - Upper Case using M LanguageExtract using Power Query and M LanguageParse XML Data using Power Query and M LanguageParse JSON Data using Power Query and M LanguageStatistics using Power Query and M LanguageStandard and Scientific using Power Query and M LanguageTrigonometry - Rounding - Information using Power Query and M LanguageDate Transformation using Power Query and M Language-0Date Transformation using Power Query and M Language-1Time- Duration Transformation using Power Query and M LanguageQuery Setting in View Tab-0Query Setting in View Tab-1Data Preview 1 in View TabData Preview 2 in View TabCreate Calendar using M Language and DAXPower Query Best Practices-0Power Query Best Practices-1Power Query Best Practices-2Mega searchable tutorials o Power BI, DAX, SQL and Power QueryBest Practices Power BI-0Best Practices Power BI-1Best Practices Power BI-2Best Practices Power BI-3Best Practices Power BI-4Best Practices Power BI-5DIAD - IntroductionDIAD - Accessing DataDIAD - Data Prepration-0DIAD - Data Prepration-1DIAD -Data Modeling and Exploration-0DIAD -Data Modeling and Exploration-1DIAD -Data Modeling and Exploration-2DIAD -Data Modeling and Exploration-3DIAD -Data Modeling and Exploration-4DIAD - Data Visualization-0DIAD - Data Visualization-1DIAD - Publishing ReportDIAD - Creating DashboardsDIAD - Creating Dashboards-0DIAD - Creating Dashboards-1
Overview
Section 1: Introduction
Lecture 1 What are you going to learn in this course
Lecture 2 Thank you and how to get support
Section 2: Power Query Introduction
Lecture 3 What is Power Query
Lecture 4 Why M$ created Power Query and Why use it
Lecture 5 Power Query Interface Components
Section 3: Introduction to M Language
Lecture 6 First things first
Lecture 7 What is M Language.
Lecture 8 M Language Syntax
Lecture 9 M Language Type Structures Values
Lecture 10 M Language Type Primitive Values
Lecture 11 M Language Operators
Lecture 12 What are Lists and how to create them using M Language
Lecture 13 What are Tables and Records
Section 4: Home Tab in Power Query
Lecture 14 Create initial pbix file
Lecture 15 Close and Apply
Lecture 16 New and Recent Sources-0
Lecture 17 New and Recent Sources-1
Lecture 18 Data Source and Privacy Settings
Lecture 19 Using Parameters in Report-0
Lecture 20 Using Parameters in Report-1
Lecture 21 Using Parameters as File Path or Data Source
Lecture 22 Query Options
Lecture 23 Manage Column using M Language
Lecture 24 Reduce Rows using Power Query
Lecture 25 Reduce Rows using M Language
Lecture 26 Sort Order for Data and Filters using Power Query
Lecture 27 Sort Order for Data using M Language
Lecture 28 Split Column using Power Query
Lecture 29 Split Column using M Language
Lecture 30 Group by or Grouping Data using Power Query-0
Lecture 31 Group by or Grouping Data using Power Query-1
Lecture 32 Group by using M Language
Lecture 33 Data Type using Power Query and M
Lecture 34 Headers as first row and First row as Headers using Power Query and M
Lecture 35 Replace Values using Power Query and M
Lecture 36 Merge Tables using Power Query-0
Lecture 37 Merge Tables using Power Query-1
Lecture 38 Append Tables using Power Query-0
Lecture 39 Append Tables using Power Query-1
Section 5: Transform Tab in Power Query
Lecture 40 Group by or Grouping Data using Power Query-0
Lecture 41 Group by or Grouping Data using Power Query-1
Lecture 42 Headers as first row and First row as Headers using Power Query and M
Lecture 43 Transpose-Reverse-Count Rows using Power Query and M
Lecture 44 Data Type and Rename using Power Query and M
Lecture 45 Replace - Fill using Power Query and M
Lecture 46 Pivot - Unpivoting using Power Query
Lecture 47 Move - Convert to List using Power Query
Lecture 48 Split Column using Power Query 0
Lecture 49 Split Column using Power Query 1
Lecture 50 Split Column using M Language
Lecture 51 Format - Trim - clean -Lower - Upper Case using Power Query
Lecture 52 Format - Trim - clean -Lower - Upper Case using M Language
Lecture 53 Merge Columns using Power Query and M Language
Lecture 54 Extract using Power Query and M Language
Lecture 55 Parse XML Data using Power Query and M Language
Lecture 56 Parse JSON Data using Power Query and M Language
Lecture 57 Statistics using Power Query and M Language
Lecture 58 Standard and Scientific using Power Query and M Language
Lecture 59 Trigonometry - Rounding - Information using Power Query and M Language-0
Lecture 60 Trigonometry - Rounding - Information using Power Query and M Language-1
Lecture 61 Date Transformation using Power Query and M Language-0
Lecture 62 Date Transformation using Power Query and M Language-1
Lecture 63 Time-Duration Transformation using Power Query and M Language
Section 6: AddColumn Tab in Power Query
Lecture 64 Column From Example using Power Query and M Language
Lecture 65 Custom Column using Power Query and M Language-0
Lecture 66 Custom Column using Power Query and M Language-1
Lecture 67 Invoke Custom Column using Power Query and M Language-0
Lecture 68 Invoke Custom Column using Power Query and M Language-1
Lecture 69 Conditional Column using Power Query and M Language
Lecture 70 Index Column using Power Query and M Language-0
Lecture 71 Index Column using Power Query and M Language-1
Lecture 72 Duplicate and Merge Column using Power Query and M Language
Lecture 73 Format - Trim - clean -Lower - Upper Case using Power Query
Lecture 74 Format - Trim - clean -Lower - Upper Case using M Language
Lecture 75 Extract using Power Query and M Language
Lecture 76 Parse XML Data using Power Query and M Language
Lecture 77 Parse JSON Data using Power Query and M Language
Lecture 78 Statistics using Power Query and M Language
Lecture 79 Standard and Scientific using Power Query and M Language
Lecture 80 Trigonometry - Rounding - Information using Power Query and M Language
Lecture 81 Date Transformation using Power Query and M Language-0
Lecture 82 Date Transformation using Power Query and M Language-1
Lecture 83 Time- Duration Transformation using Power Query and M Language
Section 7: View Tab in Power Query
Lecture 84 Query Setting in View Tab-0
Lecture 85 Query Setting in View Tab-1
Lecture 86 Data Preview 1 in View Tab
Lecture 87 Data Preview 2 in View Tab
Section 8: Create Date Table using M language and Dax
Lecture 88 Create Calendar using M Language and DAX
Section 9: Power Query Best Practices
Lecture 89 Power Query Best Practices-0
Lecture 90 Power Query Best Practices-1
Lecture 91 Power Query Best Practices-2
Section 10: Mega searchable tutorials on Power BI, DAX, SQL and Power Query
Lecture 92 Mega searchable tutorials o Power BI, DAX, SQL and Power Query
Section 11: AI Visuals - ChatGPT and Microsoft CoPilot
Lecture 93 Decomposition Tree Visual
Lecture 94 Key Influencers Visual
Lecture 95 Smart Narrative
Lecture 96 QA Visual
Lecture 97 Quick Measures with CoPilot
Lecture 98 Column from Examples
Lecture 99 New Calculation (Measures) - Model Tab
Lecture 100 Field Parameters (Dynamic X Axis and Y Axis)
Lecture 101 Bravo Tool
Lecture 102 ChatGPT - Power BI CoPilot DAX Example
Lecture 103 ChatGPT - Power BI CoPilot M Code Example
Section 12: Additional contents - Best Practices Power BI
Lecture 104 Best Practices Power BI-0
Lecture 105 Best Practices Power BI-1
Lecture 106 Best Practices Power BI-2
Lecture 107 Best Practices Power BI-3
Lecture 108 Best Practices Power BI-4
Lecture 109 Best Practices Power BI-5
Section 13: Additional content - Dashboard in a day
Lecture 110 DIAD - Introduction
Lecture 111 DIAD - Accessing Data
Lecture 112 DIAD - Data Prepration-0
Lecture 113 DIAD - Data Prepration-1
Lecture 114 DIAD -Data Modeling and Exploration-0
Lecture 115 DIAD -Data Modeling and Exploration-1
Lecture 116 DIAD -Data Modeling and Exploration-2
Lecture 117 DIAD -Data Modeling and Exploration-3
Lecture 118 DIAD -Data Modeling and Exploration-4
Lecture 119 DIAD - Data Visualization-0
Lecture 120 DIAD - Data Visualization-1
Lecture 121 DIAD - Publishing Report
Lecture 122 DIAD - Creating Dashboards
Lecture 123 DIAD - Creating Dashboards-0
Lecture 124 DIAD - Creating Dashboards-1
This course is for beginners. we focus on taking you from beginners to advance by working on business use cases,If want to learn Power Query and M Language completely from scratch,Non technical employee who is interested in solving business challenges without writing codes,Anyone interested in business transformation using no/low code platform,Anyone that needs to import and clean data to be analyzed,Anyone who copies and pastes data into the same Excel spreadsheet on a regular basis in order to be able to continue their workflow,Individuals interested in upskilling to become more competitive and productive at work,If you know some Power Query and M Language skills but want to get better,If you are good with Power Query and M Language and want to take your skills to the next level and truly leverage the full potential of Power Query and M Language,Employees with repetitive task or seemingly manual processes and need to automate them,Students who want to upskill in preparation for job placement,Managers who is interested in what is possible with Power Platform,Young Graduate who need to add more skills to their skillset for better job placement
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What you'll learn
Understand Power Query and its components
Understand power query to connect and explore your data
How to Explore reshape and enrich your data
How to create calculated columns
How to Shape or transform data to match your data analysis requirements
How to Refresh a query to import the latest data into a table
How to Combine data from multiple data sources
How to Filter a table based on size, value, or condition
How to Sort a table ranked by a criteria, such as the alphabetical or numerical value of one or multiple columns, and by ascending or descending order.
How to Group rows in a table
How to Expand/Extend a column
How to Aggregate data from a column by group operation, including Sum, Count, Average, Min, and Max
How to Insert a custom column into a table — Insert an Index or Custom column
How to Combine multiple queries by merging or appending them
There is no coding required! Power Query allows you to do that but it's not necessary
Build complex and custom transformation
Write M code to add/delete/transform custom columns
Implement Best practice in Power Query and M language
Explore how the M language can be used to write your own customized solutions
Use custom functions to extend and enhance Power Query
Create your own formulas and functions to go beyond simple data imports
Gain effiiciency by reducing the time it takes to prepare data for analysis, and make informed decisions more quickly
Gain productivity by properly preparing data yourself, rather than relying on others to do it
Requirements
Microsoft Power BI Desktop (free download)
This course is designed for PC/Windows users (currently not available for Mac)
Your willingness to learn and grow
This is a Power Query and M Language Training for beginners to advanced
Description
Companies are gathering more and more data everyday. Skills in data analysis, business intelligence / business analytics are highly in demand in today's job market. Microsoft Power BI is an advanced yet easy to use self service Business Intelligence / business analytics tool for that. It is same business intelligence. tools used by professional analysts and data scientists. Therefore they rely heavily on data. Data driven decision making is the key to success for any business in the world of tomorrow.Imagine how much power you when you know how to clean big data. Microsoft included power query and M language Engine virtually in every data product. You will be very surprised that you did not learn this earlier.One of the advantages of technology and having the skill is the opportunity it offers to scale your business and career. To be more productive, you need to work smarter. With low-code/no-code tools Microsoft Power Query and M Language, you can extract data from different sources, clean, reshape, remove, prepare, generate new data mashup, append and merge data .This is the most comprehensive and complete course in power query. We are going to cover over hundreds of data transformations in this course. We are covering Power Query in depth in this course does. Absolutely no experience required in Power Query or M Language. We will start from the basics and gradually build up your knowledge. I will introduce you to some great features of Power query and M Language with hands on demos. after completing this course you be able to transform you data like DBAs and ETL Developers.You do not have to learn R or python anymore. I am going to teach you to become data scientist just learn power query and M because you already know how to clean data. You can follow along with the provided learning material on your own computer at your own pace. I will basically hold your hand and teach you everything step-by-step.Understand Power Query and its componentsUnderstand power query to connect and explore your dataHow to explore, reshape and enrich your dataHow to create calculated columnsHow to shape or transform data to match your data analysis requirements.How to refresh a query to import the latest data into a tableHow to combine data from multiple data sourcesHow to filter a table based on size, value, or condition.How to sort a table ranked by a criteria, such as the alphabetical or numerical value of one or multiple columns, and by ascending or descending order.How to group rows in a tableHow to expand/extend a columnHow to aggregate data from a column by group operation, including sum, count, average, min, and max.How to Insert a custom column into a table — Insert an Index or custom columnHow to Combine multiple queries by merging or appending them.There is no coding required! Power Query allows you to do that but it's not necessary.Build complex and custom transformationWrite M code to add/delete/transform custom columnsImplement best practice in Power Query and M languageThis Course Also Comes With:Lifetime access to all future updatesFast & friendly support in the Q&A sectionCustom notes, homework exercises, checklists, templates, course quizzes to help get results fasterUdemy certificate of completion ready for downloadA 30 days "no questions asked" money back guarantee!Here is list of lectures :What are you going to learn in this courseThank you and how to get supportWhat is Power QueryWhy Microsoft created Power Query and why use itPower Query Interface ComponentsFirst things firstM Language Type Structures ValuesM Language Type Primitive ValuesM Language OperatorsWhat are Lists and how to create them using M LanguageWhat are Tables and RecordsCreate initial pbix fileData Source and Privacy SettingsUsing Parameters in Report-0Using Parameters in Report-1Using Parameters as File Path or Data SourceQuery OptionsManage Column using M LanguageReduce Rows using Power QueryReduce Rows using M LanguageSort Order for Data and Filters using Power QuerySort Order for Data using M LanguageSplit Column using Power QuerySplit Column using M LanguageGroup by or Grouping Data using Power Query-0Group by or Grouping Data using Power Query-1Group by using M LanguageData Type using Power Query and MHeaders as first row and First row as Headers using Power Query and MReplace Values using Power Query and MMerge Tables using Power Query-0Merge Tables using Power Query-1Append Tables using Power Query-0Append Tables using Power Query-1Group by or Grouping Data using Power Query-0Group by or Grouping Data using Power Query-1Headers as first row and First row as Headers using Power Query and MTranspose-Reverse-Count Rows using Power Query and MData Type and Rename using Power Query and MReplace - Fill using Power Query and MPivot - Unpivoting using Power QueryMove - Convert to List using Power QuerySplit Column using Power Query 0Split Column using Power Query 1Split Column using M LanguageFormat - Trim - clean -Lower - Upper Case using Power QueryFormat - Trim - clean -Lower - Upper Case using M LanguageMerge Columns using Power Query and M LanguageExtract using Power Query and M LanguageParse XML Data using Power Query and M LanguageParse JSON Data using Power Query and M LanguageStatistics using Power Query and M LanguageStandard and Scientific using Power Query and M LanguageTrigonometry - Rounding - Information using Power Query and M Language-0Trigonometry - Rounding - Information using Power Query and M Language-1Date Transformation using Power Query and M Language-0Date Transformation using Power Query and M Language-1Time-Duration Transformation using Power Query and M LanguageColumn From Example using Power Query and M LanguageCustom Column using Power Query and M Language-0Custom Column using Power Query and M Language-1Invoke Custom Column using Power Query and M Language-0Invoke Custom Column using Power Query and M Language-1Conditional Column using Power Query and M LanguageIndex Column using Power Query and M Language-0Index Column using Power Query and M Language-1Duplicate and Merge Column using Power Query and M LanguageFormat - Trim - clean -Lower - Upper Case using Power QueryFormat - Trim - clean -Lower - Upper Case using M LanguageExtract using Power Query and M LanguageParse XML Data using Power Query and M LanguageParse JSON Data using Power Query and M LanguageStatistics using Power Query and M LanguageStandard and Scientific using Power Query and M LanguageTrigonometry - Rounding - Information using Power Query and M LanguageDate Transformation using Power Query and M Language-0Date Transformation using Power Query and M Language-1Time- Duration Transformation using Power Query and M LanguageQuery Setting in View Tab-0Query Setting in View Tab-1Data Preview 1 in View TabData Preview 2 in View TabCreate Calendar using M Language and DAXPower Query Best Practices-0Power Query Best Practices-1Power Query Best Practices-2Mega searchable tutorials o Power BI, DAX, SQL and Power QueryBest Practices Power BI-0Best Practices Power BI-1Best Practices Power BI-2Best Practices Power BI-3Best Practices Power BI-4Best Practices Power BI-5DIAD - IntroductionDIAD - Accessing DataDIAD - Data Prepration-0DIAD - Data Prepration-1DIAD -Data Modeling and Exploration-0DIAD -Data Modeling and Exploration-1DIAD -Data Modeling and Exploration-2DIAD -Data Modeling and Exploration-3DIAD -Data Modeling and Exploration-4DIAD - Data Visualization-0DIAD - Data Visualization-1DIAD - Publishing ReportDIAD - Creating DashboardsDIAD - Creating Dashboards-0DIAD - Creating Dashboards-1
Overview
Section 1: Introduction
Lecture 1 What are you going to learn in this course
Lecture 2 Thank you and how to get support
Section 2: Power Query Introduction
Lecture 3 What is Power Query
Lecture 4 Why M$ created Power Query and Why use it
Lecture 5 Power Query Interface Components
Section 3: Introduction to M Language
Lecture 6 First things first
Lecture 7 What is M Language.
Lecture 8 M Language Syntax
Lecture 9 M Language Type Structures Values
Lecture 10 M Language Type Primitive Values
Lecture 11 M Language Operators
Lecture 12 What are Lists and how to create them using M Language
Lecture 13 What are Tables and Records
Section 4: Home Tab in Power Query
Lecture 14 Create initial pbix file
Lecture 15 Close and Apply
Lecture 16 New and Recent Sources-0
Lecture 17 New and Recent Sources-1
Lecture 18 Data Source and Privacy Settings
Lecture 19 Using Parameters in Report-0
Lecture 20 Using Parameters in Report-1
Lecture 21 Using Parameters as File Path or Data Source
Lecture 22 Query Options
Lecture 23 Manage Column using M Language
Lecture 24 Reduce Rows using Power Query
Lecture 25 Reduce Rows using M Language
Lecture 26 Sort Order for Data and Filters using Power Query
Lecture 27 Sort Order for Data using M Language
Lecture 28 Split Column using Power Query
Lecture 29 Split Column using M Language
Lecture 30 Group by or Grouping Data using Power Query-0
Lecture 31 Group by or Grouping Data using Power Query-1
Lecture 32 Group by using M Language
Lecture 33 Data Type using Power Query and M
Lecture 34 Headers as first row and First row as Headers using Power Query and M
Lecture 35 Replace Values using Power Query and M
Lecture 36 Merge Tables using Power Query-0
Lecture 37 Merge Tables using Power Query-1
Lecture 38 Append Tables using Power Query-0
Lecture 39 Append Tables using Power Query-1
Section 5: Transform Tab in Power Query
Lecture 40 Group by or Grouping Data using Power Query-0
Lecture 41 Group by or Grouping Data using Power Query-1
Lecture 42 Headers as first row and First row as Headers using Power Query and M
Lecture 43 Transpose-Reverse-Count Rows using Power Query and M
Lecture 44 Data Type and Rename using Power Query and M
Lecture 45 Replace - Fill using Power Query and M
Lecture 46 Pivot - Unpivoting using Power Query
Lecture 47 Move - Convert to List using Power Query
Lecture 48 Split Column using Power Query 0
Lecture 49 Split Column using Power Query 1
Lecture 50 Split Column using M Language
Lecture 51 Format - Trim - clean -Lower - Upper Case using Power Query
Lecture 52 Format - Trim - clean -Lower - Upper Case using M Language
Lecture 53 Merge Columns using Power Query and M Language
Lecture 54 Extract using Power Query and M Language
Lecture 55 Parse XML Data using Power Query and M Language
Lecture 56 Parse JSON Data using Power Query and M Language
Lecture 57 Statistics using Power Query and M Language
Lecture 58 Standard and Scientific using Power Query and M Language
Lecture 59 Trigonometry - Rounding - Information using Power Query and M Language-0
Lecture 60 Trigonometry - Rounding - Information using Power Query and M Language-1
Lecture 61 Date Transformation using Power Query and M Language-0
Lecture 62 Date Transformation using Power Query and M Language-1
Lecture 63 Time-Duration Transformation using Power Query and M Language
Section 6: AddColumn Tab in Power Query
Lecture 64 Column From Example using Power Query and M Language
Lecture 65 Custom Column using Power Query and M Language-0
Lecture 66 Custom Column using Power Query and M Language-1
Lecture 67 Invoke Custom Column using Power Query and M Language-0
Lecture 68 Invoke Custom Column using Power Query and M Language-1
Lecture 69 Conditional Column using Power Query and M Language
Lecture 70 Index Column using Power Query and M Language-0
Lecture 71 Index Column using Power Query and M Language-1
Lecture 72 Duplicate and Merge Column using Power Query and M Language
Lecture 73 Format - Trim - clean -Lower - Upper Case using Power Query
Lecture 74 Format - Trim - clean -Lower - Upper Case using M Language
Lecture 75 Extract using Power Query and M Language
Lecture 76 Parse XML Data using Power Query and M Language
Lecture 77 Parse JSON Data using Power Query and M Language
Lecture 78 Statistics using Power Query and M Language
Lecture 79 Standard and Scientific using Power Query and M Language
Lecture 80 Trigonometry - Rounding - Information using Power Query and M Language
Lecture 81 Date Transformation using Power Query and M Language-0
Lecture 82 Date Transformation using Power Query and M Language-1
Lecture 83 Time- Duration Transformation using Power Query and M Language
Section 7: View Tab in Power Query
Lecture 84 Query Setting in View Tab-0
Lecture 85 Query Setting in View Tab-1
Lecture 86 Data Preview 1 in View Tab
Lecture 87 Data Preview 2 in View Tab
Section 8: Create Date Table using M language and Dax
Lecture 88 Create Calendar using M Language and DAX
Section 9: Power Query Best Practices
Lecture 89 Power Query Best Practices-0
Lecture 90 Power Query Best Practices-1
Lecture 91 Power Query Best Practices-2
Section 10: Mega searchable tutorials on Power BI, DAX, SQL and Power Query
Lecture 92 Mega searchable tutorials o Power BI, DAX, SQL and Power Query
Section 11: AI Visuals - ChatGPT and Microsoft CoPilot
Lecture 93 Decomposition Tree Visual
Lecture 94 Key Influencers Visual
Lecture 95 Smart Narrative
Lecture 96 QA Visual
Lecture 97 Quick Measures with CoPilot
Lecture 98 Column from Examples
Lecture 99 New Calculation (Measures) - Model Tab
Lecture 100 Field Parameters (Dynamic X Axis and Y Axis)
Lecture 101 Bravo Tool
Lecture 102 ChatGPT - Power BI CoPilot DAX Example
Lecture 103 ChatGPT - Power BI CoPilot M Code Example
Section 12: Additional contents - Best Practices Power BI
Lecture 104 Best Practices Power BI-0
Lecture 105 Best Practices Power BI-1
Lecture 106 Best Practices Power BI-2
Lecture 107 Best Practices Power BI-3
Lecture 108 Best Practices Power BI-4
Lecture 109 Best Practices Power BI-5
Section 13: Additional content - Dashboard in a day
Lecture 110 DIAD - Introduction
Lecture 111 DIAD - Accessing Data
Lecture 112 DIAD - Data Prepration-0
Lecture 113 DIAD - Data Prepration-1
Lecture 114 DIAD -Data Modeling and Exploration-0
Lecture 115 DIAD -Data Modeling and Exploration-1
Lecture 116 DIAD -Data Modeling and Exploration-2
Lecture 117 DIAD -Data Modeling and Exploration-3
Lecture 118 DIAD -Data Modeling and Exploration-4
Lecture 119 DIAD - Data Visualization-0
Lecture 120 DIAD - Data Visualization-1
Lecture 121 DIAD - Publishing Report
Lecture 122 DIAD - Creating Dashboards
Lecture 123 DIAD - Creating Dashboards-0
Lecture 124 DIAD - Creating Dashboards-1
This course is for beginners. we focus on taking you from beginners to advance by working on business use cases,If want to learn Power Query and M Language completely from scratch,Non technical employee who is interested in solving business challenges without writing codes,Anyone interested in business transformation using no/low code platform,Anyone that needs to import and clean data to be analyzed,Anyone who copies and pastes data into the same Excel spreadsheet on a regular basis in order to be able to continue their workflow,Individuals interested in upskilling to become more competitive and productive at work,If you know some Power Query and M Language skills but want to get better,If you are good with Power Query and M Language and want to take your skills to the next level and truly leverage the full potential of Power Query and M Language,Employees with repetitive task or seemingly manual processes and need to automate them,Students who want to upskill in preparation for job placement,Managers who is interested in what is possible with Power Platform,Young Graduate who need to add more skills to their skillset for better job placement
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