Power BI Desktop Combo - Query Editor, Data Modelling, DAX

  • Course provided by Udemy
  • Study type: Online
  • Starts: Anytime
  • Price: See latest price on Udemy
Udemy

Course Description

Microsoft Power BI is a suite of Business Intelligence tools, designed to help the BI professionals get easier, quick and crucial business insights from their data. It contains three main tool-set combined in one single software:

  • Power Query

  • Power Pivot

  • Power View

Power Query lets you to connect to hundreds of data sources, simplify data preparation and drive ad-hoc analysis. It is also know as Power BI Query Editor.

Power Pivot is the analytical tool in Power BI. Using various DAX formulas you can drive your analytical journey. This is the second step after you import the data into Power BI using Power BI Query Editor.

This course will focus completely on features for Power BI Query Editor, Date Modelling and DAX inside Power BI Desktop.

Before you can present any analysis or insight, you need source data. Your source data could be in many places and in many formats. Nonetheless, you need to access it, look at it, and quite possibly clean it up to some extent. You may also need to join separate data sources before you can shape the data into a coherent data set using PowerPivot, deliver the results using Power View or Power Map, and then share it using Power BI.

Discovering, loading, cleaning, and modifying source data is where Power BI Query editor comes in. It lets you load, shape and streamline data from multiple sources.

Power BI Query Editor allows you to do many things with source data, but the four main steps are likely to be

  • Import data from a wide variety of sources. This covers corporate databases to files, and social media to big data.

  • Merge data from multiple sources into a coherent structure.

  • Shape data into the columns and records that suit your uses.

  • Cleanse your data to make it reliable and easy to use.

There was a time when these processes required dedicated teams of IT specialists. Well, not any more. With Power Query, you can mash up your own data so that it is the way you want it and is ready to use as part of your self-service BI solution.

This course will start with the basic installation and configuration of Power BI Desktop, and go on to connect your data sources with it. You’ll transform and get your data ready for analysis, and create effective data views using it. You would be performing following tasks mainly

  • Data Discovery —Find and connect to a myriad of data sources containing potentially useful data. This can be from both public and private data sources.

  • Data Loading —Select the data you have examined and load it into Power Query for shaping.

  • Data Modification —Modify the structure of each data table that you have imported, filter and clean the data itself, and then join any separate data sources.


Although I have outlined these three steps as if they are completely separate and sequential, the reality is that they often blend into a single process. Indeed there could be many occasions when you will examine the data after it has been loaded into Power Query—or join data tables before you clean them. The core objective will, however, always remain the same: find some data and then load it into Power Query where you can tweak, clean, and shape it.

This process could be described simplistically as “First, catch your data.” In the world of data warehousing, the specialists call it ETL, which is short for Extract Transform Load. Despite the reassuring confidence that the acronym brings, this process is rarely a smooth logical progression through a clear-cut series of processes. The reality is often far messier than that. You may often find yourself importing some data, cleaning it, importing some more data from another source, combining the second data set with the first one, cleaning some more, and then repeating many of these operations several times.

This course will excite and empower you to get more out of Power BI Query Editor via detailed recipes, development tips and guidance on enhancing existing Power BI Projects.

Who this course is for:

  • Users who have used or have started using Power BI.
  • Person looking for easy alternative to Excel or any other ETL software
  • This course is for Beginners to pro users as well.
  • People who want to automate their data preparation task for within Power BI
  • You will master the data cleansing tasks from Power BI Query editor Proven development techniques and guidance for implementing custom solutions with M language Build efficient data retrieval and transformation processes with the M Query Language Requirements Person who is really struggling with Data Cleansing tasks and looking for robust solution. Have used or started using Power BI and want to master data cleansing techniques. Need to install Power BI Desktop (only available for Windows) Description Microsoft Power BI is a suite of Business Intelligence tools, designed to help the BI professionals get easier, quick and crucial business insights from their data. It contains three main tool-set combined in one single software: Power Query Power Pivot Power View Power Query lets you to connect to hundreds of data sources, simplify data preparation and drive ad-hoc analysis. It is also know as Power BI Query Editor. Power Pivot is the analytical tool in Power BI. Using various DAX formulas you can drive your analytical journey. This is the second step after you import the data into Power BI using Power BI Query Editor. This course will focus completely on features for Power BI Query Editor, Date Modelling and DAX inside Power BI Desktop. Before you can present any analysis or insight, you need source data. Your source data could be in many places and in many formats. Nonetheless, you need to access it, look at it, and quite possibly clean it up to some extent. You may also need to join separate data sources before you can shape the data into a coherent data set using PowerPivot, deliver the results using Power View or Power Map, and then share it using Power BI. Discovering, loading, cleaning, and modifying source data is where Power BI Query editor comes in. It lets you load, shape and streamline data from multiple sources. Power BI Query Editor allows you to do many things with source data, but the four main steps are likely to be Import data from a wide variety of sources. This covers corporate databases to files, and social media to big data. Merge data from multiple sources into a coherent structure. Shape data into the columns and records that suit your uses. Cleanse your data to make it reliable and easy to use. There was a time when these processes required dedicated teams of IT specialists. Well, not any more. With Power Query, you can mash up your own data so that it is the way you want it and is ready to use as part of your self-service BI solution. This course will start with the basic installation and configuration of Power BI Desktop, and go on to connect your data sources with it. You’ll transform and get your data ready for analysis, and create effective data views using it. You would be performing following tasks mainly Data Discovery —Find and connect to a myriad of data sources containing potentially useful data. This can be from both public and private data sources. Data Loading —Select the data you have examined and load it into Power Query for shaping. Data Modification —Modify the structure of each data table that you have imported, filter and clean the data itself, and then join any separate data sources. Although I have outlined these three steps as if they are completely separate and sequential, the reality is that they often blend into a single process. Indeed there could be many occasions when you will examine the data after it has been loaded into Power Query—or join data tables before you clean them. The core objective will, however, always remain the same: find some data and then load it into Power Query where you can tweak, clean, and shape it. This process could be described simplistically as “First, catch your data.” In the world of data warehousing, the specialists call it ETL, which is short for Extract Transform Load. Despite the reassuring confidence that the acronym brings, this process is rarely a smooth logical progression through a clear-cut series of processes. The reality is often far messier than that. You may often find yourself importing some data, cleaning it, importing some more data from another source, combining the second data set with the first one, cleaning some more, and then repeating many of these operations several times. This course will excite and empower you to get more out of Power BI Query Editor via detailed recipes, development tips and guidance on enhancing existing Power BI Projects. Who this course is for: Users who have used or have started using Power BI. Person looking for easy alternative to Excel or any other ETL software This course is for Beginners to pro users as well. People who want to automate their data preparation task for within Power BI Show more Show less Course content 15 sections • 104 lectures • 11h 50m total length Expand all sections Introduction 4 lectures • 22min Introduction to Power BI and Query Editor Preview 07:26 Download and Install Power BI Desktop Preview 05:05 Getting familiar with Power BI desktop and Query Editor 09:18 About the course and more videos being added Preview 00:22 Importing Data into Power BI 5 lectures • 27min Import Data from Excel File Preview 07:06 Import data from Text - Tab delimited file 03:08 Import data from CSV delimited file 04:35 Import data from Access files 03:39 Loading data to data model and file path changes 08:46 Transformation in built in Query ribbon 3 lectures • 35min In built Column Transformation 15:54 In built Row transformations 10:02 Filtering selected rows in Power Query 09:08 Other in built transformation 4 lectures • 44min Text Transformation 12:16 Numbers transformation 13:53 Date transformation 09:52 Conditional Columns 08:15 Multiple data source / queries 5 lectures • 27min Introduction to Append / Duplicate / Reference Queries 02:40 Append multiple files individually with different queries 05:25 Importing multiple files from a folder using single query 06:43 Append the Data from multiple excel sheets and multiples files in folder 06:26 Duplicate / Reference queries - Differences and usage 05:46 Merge Queries / Multiple Joins in Power Query 4 lectures • 31min Left, Right and Outer joins 08:19 Left, Right, Outer joins - Part 1 09:31 Left, Right Anti joins - Part 2 06:03 Cross Joins / Cartesian Product using other functions 07:26 Building blocks for M language 5 lectures • 49min Introduction to building blocks in M 05:11 Text functions in M 14:02 Date functions in M 08:48 Conditional functions in M - IF, AND, OR 12:01 Column from example 09:00 Case Studies - Part 1 7 lectures • 55min Financial Statements 07:33 Payroll Data 08:34 Stacked data to columnar data - Address Book 07:34 Multiple filters on single column 06:42 Rows to columnar data set 07:45 Looking up discount rates 12:02 Invoice data 05:00 Power Query Objects 5 lectures • 27min Power Query Objects Introduction 00:54 List as object and List functions in Power Query 12:30 Record as object and Record functions in Power Query 09:32 Table & other objects and Table functions in Power Query 03:10 Power Query Objects - Recap 01:15 Advanced Case Studies - Part 2 6 lectures • 47min Advanced Case Studies introduction 02:01 Extracting only relevant data 14:24 Creating dynamic Calendar table 09:49 Individual sales to total sales percentage 07:51 Multiple filters on a single column - part 2 03:47 Leave Data Part - Split to individual rows from range of dates 09:18 5 more sections Instructor Abhay Gadiya Best seller instructor for Power BI and Power Excel 4.3 Instructor Rating 555 Reviews 2,738 Students 7 Courses I am Chartered Accountant, Certified Fraud Examiner and have completed Diploma in Information System Audit (Indian equivalent exam for CISA). I have circa 16+ years of experience into Data Analytics, Internal Audits, External (Statutory) Audits, SOX Compliance, Risk Assessment and Regulatory Compliance. I have audited various entities under BFSI, Automotive Manufacturing, ITES, Infrastructure and Pharmaceuticals sectors. I have worked circa 9 years with Big4 consultancy firms – Deloitte, Price Waterhouse and other with Bank of New York Mellon. I have conducted various workshops at Institute of Chartered Accountants of India. Approximately 600+ people have attended these workshops and have given extremely positive feedback. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'67819b4f3e6b5440',m:'6789b5e6fd429d3f8ab56ebb34e0daf98751f330-1627847545-1800-ATcQGrssND55nrtxmfzVUHyi8Xl9JYmEs280TKobqkvxd4NwxAB1+LrIOdJX/KW84m3ei0hAFV/rMI433ea3/CklZxGwXk/+/H/xAO5FZU0MypbYdAltH4o8v14spMzmpMl+WYe/sMqmTxRLseHLtt3K5RYFbWO88IWN4JSnESZstewymqz1YfGIXIL9VCdBgvEfgOLzQpST/dviQZ+hNMY=',s:[0xdda8a03d29,0x391d5108d1],}})();
  • Proven development techniques and guidance for implementing custom solutions with M language Build efficient data retrieval and transformation processes with the M Query Language Requirements Person who is really struggling with Data Cleansing tasks and looking for robust solution. Have used or started using Power BI and want to master data cleansing techniques. Need to install Power BI Desktop (only available for Windows) Description Microsoft Power BI is a suite of Business Intelligence tools, designed to help the BI professionals get easier, quick and crucial business insights from their data. It contains three main tool-set combined in one single software: Power Query Power Pivot Power View Power Query lets you to connect to hundreds of data sources, simplify data preparation and drive ad-hoc analysis. It is also know as Power BI Query Editor. Power Pivot is the analytical tool in Power BI. Using various DAX formulas you can drive your analytical journey. This is the second step after you import the data into Power BI using Power BI Query Editor. This course will focus completely on features for Power BI Query Editor, Date Modelling and DAX inside Power BI Desktop. Before you can present any analysis or insight, you need source data. Your source data could be in many places and in many formats. Nonetheless, you need to access it, look at it, and quite possibly clean it up to some extent. You may also need to join separate data sources before you can shape the data into a coherent data set using PowerPivot, deliver the results using Power View or Power Map, and then share it using Power BI. Discovering, loading, cleaning, and modifying source data is where Power BI Query editor comes in. It lets you load, shape and streamline data from multiple sources. Power BI Query Editor allows you to do many things with source data, but the four main steps are likely to be Import data from a wide variety of sources. This covers corporate databases to files, and social media to big data. Merge data from multiple sources into a coherent structure. Shape data into the columns and records that suit your uses. Cleanse your data to make it reliable and easy to use. There was a time when these processes required dedicated teams of IT specialists. Well, not any more. With Power Query, you can mash up your own data so that it is the way you want it and is ready to use as part of your self-service BI solution. This course will start with the basic installation and configuration of Power BI Desktop, and go on to connect your data sources with it. You’ll transform and get your data ready for analysis, and create effective data views using it. You would be performing following tasks mainly Data Discovery —Find and connect to a myriad of data sources containing potentially useful data. This can be from both public and private data sources. Data Loading —Select the data you have examined and load it into Power Query for shaping. Data Modification —Modify the structure of each data table that you have imported, filter and clean the data itself, and then join any separate data sources. Although I have outlined these three steps as if they are completely separate and sequential, the reality is that they often blend into a single process. Indeed there could be many occasions when you will examine the data after it has been loaded into Power Query—or join data tables before you clean them. The core objective will, however, always remain the same: find some data and then load it into Power Query where you can tweak, clean, and shape it. This process could be described simplistically as “First, catch your data.” In the world of data warehousing, the specialists call it ETL, which is short for Extract Transform Load. Despite the reassuring confidence that the acronym brings, this process is rarely a smooth logical progression through a clear-cut series of processes. The reality is often far messier than that. You may often find yourself importing some data, cleaning it, importing some more data from another source, combining the second data set with the first one, cleaning some more, and then repeating many of these operations several times. This course will excite and empower you to get more out of Power BI Query Editor via detailed recipes, development tips and guidance on enhancing existing Power BI Projects. Who this course is for: Users who have used or have started using Power BI. Person looking for easy alternative to Excel or any other ETL software This course is for Beginners to pro users as well. People who want to automate their data preparation task for within Power BI Show more Show less Course content 15 sections • 104 lectures • 11h 50m total length Expand all sections Introduction 4 lectures • 22min Introduction to Power BI and Query Editor Preview 07:26 Download and Install Power BI Desktop Preview 05:05 Getting familiar with Power BI desktop and Query Editor 09:18 About the course and more videos being added Preview 00:22 Importing Data into Power BI 5 lectures • 27min Import Data from Excel File Preview 07:06 Import data from Text - Tab delimited file 03:08 Import data from CSV delimited file 04:35 Import data from Access files 03:39 Loading data to data model and file path changes 08:46 Transformation in built in Query ribbon 3 lectures • 35min In built Column Transformation 15:54 In built Row transformations 10:02 Filtering selected rows in Power Query 09:08 Other in built transformation 4 lectures • 44min Text Transformation 12:16 Numbers transformation 13:53 Date transformation 09:52 Conditional Columns 08:15 Multiple data source / queries 5 lectures • 27min Introduction to Append / Duplicate / Reference Queries 02:40 Append multiple files individually with different queries 05:25 Importing multiple files from a folder using single query 06:43 Append the Data from multiple excel sheets and multiples files in folder 06:26 Duplicate / Reference queries - Differences and usage 05:46 Merge Queries / Multiple Joins in Power Query 4 lectures • 31min Left, Right and Outer joins 08:19 Left, Right, Outer joins - Part 1 09:31 Left, Right Anti joins - Part 2 06:03 Cross Joins / Cartesian Product using other functions 07:26 Building blocks for M language 5 lectures • 49min Introduction to building blocks in M 05:11 Text functions in M 14:02 Date functions in M 08:48 Conditional functions in M - IF, AND, OR 12:01 Column from example 09:00 Case Studies - Part 1 7 lectures • 55min Financial Statements 07:33 Payroll Data 08:34 Stacked data to columnar data - Address Book 07:34 Multiple filters on single column 06:42 Rows to columnar data set 07:45 Looking up discount rates 12:02 Invoice data 05:00 Power Query Objects 5 lectures • 27min Power Query Objects Introduction 00:54 List as object and List functions in Power Query 12:30 Record as object and Record functions in Power Query 09:32 Table & other objects and Table functions in Power Query 03:10 Power Query Objects - Recap 01:15 Advanced Case Studies - Part 2 6 lectures • 47min Advanced Case Studies introduction 02:01 Extracting only relevant data 14:24 Creating dynamic Calendar table 09:49 Individual sales to total sales percentage 07:51 Multiple filters on a single column - part 2 03:47 Leave Data Part - Split to individual rows from range of dates 09:18 5 more sections Instructor Abhay Gadiya Best seller instructor for Power BI and Power Excel 4.3 Instructor Rating 555 Reviews 2,738 Students 7 Courses I am Chartered Accountant, Certified Fraud Examiner and have completed Diploma in Information System Audit (Indian equivalent exam for CISA). I have circa 16+ years of experience into Data Analytics, Internal Audits, External (Statutory) Audits, SOX Compliance, Risk Assessment and Regulatory Compliance. I have audited various entities under BFSI, Automotive Manufacturing, ITES, Infrastructure and Pharmaceuticals sectors. I have worked circa 9 years with Big4 consultancy firms – Deloitte, Price Waterhouse and other with Bank of New York Mellon. I have conducted various workshops at Institute of Chartered Accountants of India. Approximately 600+ people have attended these workshops and have given extremely positive feedback. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'67819b4f3e6b5440',m:'6789b5e6fd429d3f8ab56ebb34e0daf98751f330-1627847545-1800-ATcQGrssND55nrtxmfzVUHyi8Xl9JYmEs280TKobqkvxd4NwxAB1+LrIOdJX/KW84m3ei0hAFV/rMI433ea3/CklZxGwXk/+/H/xAO5FZU0MypbYdAltH4o8v14spMzmpMl+WYe/sMqmTxRLseHLtt3K5RYFbWO88IWN4JSnESZstewymqz1YfGIXIL9VCdBgvEfgOLzQpST/dviQZ+hNMY=',s:[0xdda8a03d29,0x391d5108d1],}})();
  • Build efficient data retrieval and transformation processes with the M Query Language Requirements Person who is really struggling with Data Cleansing tasks and looking for robust solution. Have used or started using Power BI and want to master data cleansing techniques. Need to install Power BI Desktop (only available for Windows) Description Microsoft Power BI is a suite of Business Intelligence tools, designed to help the BI professionals get easier, quick and crucial business insights from their data. It contains three main tool-set combined in one single software: Power Query Power Pivot Power View Power Query lets you to connect to hundreds of data sources, simplify data preparation and drive ad-hoc analysis. It is also know as Power BI Query Editor. Power Pivot is the analytical tool in Power BI. Using various DAX formulas you can drive your analytical journey. This is the second step after you import the data into Power BI using Power BI Query Editor. This course will focus completely on features for Power BI Query Editor, Date Modelling and DAX inside Power BI Desktop. Before you can present any analysis or insight, you need source data. Your source data could be in many places and in many formats. Nonetheless, you need to access it, look at it, and quite possibly clean it up to some extent. You may also need to join separate data sources before you can shape the data into a coherent data set using PowerPivot, deliver the results using Power View or Power Map, and then share it using Power BI. Discovering, loading, cleaning, and modifying source data is where Power BI Query editor comes in. It lets you load, shape and streamline data from multiple sources. Power BI Query Editor allows you to do many things with source data, but the four main steps are likely to be Import data from a wide variety of sources. This covers corporate databases to files, and social media to big data. Merge data from multiple sources into a coherent structure. Shape data into the columns and records that suit your uses. Cleanse your data to make it reliable and easy to use. There was a time when these processes required dedicated teams of IT specialists. Well, not any more. With Power Query, you can mash up your own data so that it is the way you want it and is ready to use as part of your self-service BI solution. This course will start with the basic installation and configuration of Power BI Desktop, and go on to connect your data sources with it. You’ll transform and get your data ready for analysis, and create effective data views using it. You would be performing following tasks mainly Data Discovery —Find and connect to a myriad of data sources containing potentially useful data. This can be from both public and private data sources. Data Loading —Select the data you have examined and load it into Power Query for shaping. Data Modification —Modify the structure of each data table that you have imported, filter and clean the data itself, and then join any separate data sources. Although I have outlined these three steps as if they are completely separate and sequential, the reality is that they often blend into a single process. Indeed there could be many occasions when you will examine the data after it has been loaded into Power Query—or join data tables before you clean them. The core objective will, however, always remain the same: find some data and then load it into Power Query where you can tweak, clean, and shape it. This process could be described simplistically as “First, catch your data.” In the world of data warehousing, the specialists call it ETL, which is short for Extract Transform Load. Despite the reassuring confidence that the acronym brings, this process is rarely a smooth logical progression through a clear-cut series of processes. The reality is often far messier than that. You may often find yourself importing some data, cleaning it, importing some more data from another source, combining the second data set with the first one, cleaning some more, and then repeating many of these operations several times. This course will excite and empower you to get more out of Power BI Query Editor via detailed recipes, development tips and guidance on enhancing existing Power BI Projects. Who this course is for: Users who have used or have started using Power BI. Person looking for easy alternative to Excel or any other ETL software This course is for Beginners to pro users as well. People who want to automate their data preparation task for within Power BI Show more Show less Course content 15 sections • 104 lectures • 11h 50m total length Expand all sections Introduction 4 lectures • 22min Introduction to Power BI and Query Editor Preview 07:26 Download and Install Power BI Desktop Preview 05:05 Getting familiar with Power BI desktop and Query Editor 09:18 About the course and more videos being added Preview 00:22 Importing Data into Power BI 5 lectures • 27min Import Data from Excel File Preview 07:06 Import data from Text - Tab delimited file 03:08 Import data from CSV delimited file 04:35 Import data from Access files 03:39 Loading data to data model and file path changes 08:46 Transformation in built in Query ribbon 3 lectures • 35min In built Column Transformation 15:54 In built Row transformations 10:02 Filtering selected rows in Power Query 09:08 Other in built transformation 4 lectures • 44min Text Transformation 12:16 Numbers transformation 13:53 Date transformation 09:52 Conditional Columns 08:15 Multiple data source / queries 5 lectures • 27min Introduction to Append / Duplicate / Reference Queries 02:40 Append multiple files individually with different queries 05:25 Importing multiple files from a folder using single query 06:43 Append the Data from multiple excel sheets and multiples files in folder 06:26 Duplicate / Reference queries - Differences and usage 05:46 Merge Queries / Multiple Joins in Power Query 4 lectures • 31min Left, Right and Outer joins 08:19 Left, Right, Outer joins - Part 1 09:31 Left, Right Anti joins - Part 2 06:03 Cross Joins / Cartesian Product using other functions 07:26 Building blocks for M language 5 lectures • 49min Introduction to building blocks in M 05:11 Text functions in M 14:02 Date functions in M 08:48 Conditional functions in M - IF, AND, OR 12:01 Column from example 09:00 Case Studies - Part 1 7 lectures • 55min Financial Statements 07:33 Payroll Data 08:34 Stacked data to columnar data - Address Book 07:34 Multiple filters on single column 06:42 Rows to columnar data set 07:45 Looking up discount rates 12:02 Invoice data 05:00 Power Query Objects 5 lectures • 27min Power Query Objects Introduction 00:54 List as object and List functions in Power Query 12:30 Record as object and Record functions in Power Query 09:32 Table & other objects and Table functions in Power Query 03:10 Power Query Objects - Recap 01:15 Advanced Case Studies - Part 2 6 lectures • 47min Advanced Case Studies introduction 02:01 Extracting only relevant data 14:24 Creating dynamic Calendar table 09:49 Individual sales to total sales percentage 07:51 Multiple filters on a single column - part 2 03:47 Leave Data Part - Split to individual rows from range of dates 09:18 5 more sections Instructor Abhay Gadiya Best seller instructor for Power BI and Power Excel 4.3 Instructor Rating 555 Reviews 2,738 Students 7 Courses I am Chartered Accountant, Certified Fraud Examiner and have completed Diploma in Information System Audit (Indian equivalent exam for CISA). I have circa 16+ years of experience into Data Analytics, Internal Audits, External (Statutory) Audits, SOX Compliance, Risk Assessment and Regulatory Compliance. I have audited various entities under BFSI, Automotive Manufacturing, ITES, Infrastructure and Pharmaceuticals sectors. I have worked circa 9 years with Big4 consultancy firms – Deloitte, Price Waterhouse and other with Bank of New York Mellon. I have conducted various workshops at Institute of Chartered Accountants of India. Approximately 600+ people have attended these workshops and have given extremely positive feedback. Show more Show less Udemy Business Teach on Udemy Get the app About us Contact us Careers Blog Help and Support Affiliate Impressum Kontakt Terms Privacy policy Cookie settings Sitemap © 2021 Udemy, Inc. window.handleCSSToggleButtonClick = function (event) { var target = event.currentTarget; var cssToggleId = target && target.dataset && target.dataset.cssToggleId; var input = cssToggleId && document.getElementById(cssToggleId); if (input) { if (input.dataset.type === 'checkbox') { input.dataset.checked = input.dataset.checked ? '' : 'checked'; } else { input.dataset.checked = input.dataset.allowToggle && input.dataset.checked ? '' : 'checked'; var radios = document.querySelectorAll('[name="' + input.dataset.name + '"]'); for (var i = 0; i (function(){window['__CF$cv$params']={r:'67819b4f3e6b5440',m:'6789b5e6fd429d3f8ab56ebb34e0daf98751f330-1627847545-1800-ATcQGrssND55nrtxmfzVUHyi8Xl9JYmEs280TKobqkvxd4NwxAB1+LrIOdJX/KW84m3ei0hAFV/rMI433ea3/CklZxGwXk/+/H/xAO5FZU0MypbYdAltH4o8v14spMzmpMl+WYe/sMqmTxRLseHLtt3K5RYFbWO88IWN4JSnESZstewymqz1YfGIXIL9VCdBgvEfgOLzQpST/dviQZ+hNMY=',s:[0xdda8a03d29,0x391d5108d1],}})();