{
  "video_id": "mRCIFEiFUU4",
  "channel_slug": "fahadhussaintutorial",
  "channel_handle": "fahadhussaintutorial",
  "title": "Lesson 19: View Tab in Power BI Power Query Editor | Power BI Step-by-Step Tutorial",
  "duration_seconds": 619.0,
  "url": "https://www.youtube.com/watch?v=mRCIFEiFUU4",
  "upload_date": "",
  "transcript": "Hi, welcome back again. In this session,\nwe are going to start to understand a\nview tab in power query editor. As\nusual, we are understanding from the\nstart of the power query editor. When\nyou upload the data, we can uh\nstandardize the data, we can clean the\ndata. So, this option normally used. So,\nthis time I'm using the sample data to\nunderstand the power query editor option\nview. Okay, just first load the\nfinancial data and after that I'm just\nmoving toward the power query editor.\nJust click on the transform data. Okay,\nthis sheet will be open in a power query\neditor. Uh as we know about that we can\nchange the name of the data uh I mean\ndata set. There are different columns on\nit that's start from segment to onward.\nOkay, different number of the columns\nare there. Now uh highly recommend you\nall the video session which is available\non my YouTube channel that's our\npractises to understand these topic\nwhich I'm going to start right now or in\na coming days so you need to search on\nuh me fathers and cs by the name of the\nYouTube there's my YouTube channel come\nto the playlist you can explore all the\nplaylist including the powerbi codes and\nall the things that's related to a\ncontent related material available on my\nblog fadusblogpot.com\nfrom there you can freely download and\nenjoy this data So let's say uh I'm now\nin a view tab. Okay, that is start\nthat's a very small kind of the option\nin a view tab. The first option on the\nleft corner is called a query setting.\nWhat is a query setting? By the way, at\nthe starting uh query setting in on the\nright hand side, we understand that we\ncan uh change the name of the data set\nby just double click and change it and\nthere is applied uh fields or applied\nsteps are there. Whatever you are doing\nthe log or the history are made under\nthis body. Okay. So this is option. And\nif you just cancel this one from this to\nsign. So in the view tab just click on\nthe query string or setting I mean uh\nthis option will be enabled here. And\nafter that you can cancel it out and\nthere is a setting sign as well. You\nclick on it and the setting option will\nbe available which mean that in a\nnavigation you are applying a financial\ndata. Okay. There is a financial data uh\nset in which you are just navigation\navailable. You are navigating which\nmeans okay. Uh I just cancel this one.\nUh then the next option is a formula\nbar. Uh there is a formula bar there as\nlike excel f of x function of x. So it\nis a data analysis expression dex\ncommand is here. Every time when you\napplied any option on it, so the command\nof the dex will create it by itself.\nOkay. If you want to uh hide this\nformula bar, so you need to just just\nclick on this checkbox. Okay. It will\nhide otherwise you can still show this\none by clicking on this option. A\nmonospace uh actually is a style of the\nfont. You can easily observe that the\nfont is purely and more emphasized\nmanner is showing if you just checked it\notherwise it's a default one. It's look\nlike a very dull kind of the data. Okay.\nSo that is a good practice to uh check\nthis option every time. Huh. Show white\nspace. If there is a white space it will\nshow okay uh if there is a requirement\nyou may use it otherwise there is no\nrequirement. Uh column quality. Okay\nthat's a very smart option by the way.\ncolumn colony that shows that how many\nvalid or empty data sets are there and\nhow many error are there in a separate\ncolumn. So you can observe that by using\na uh own data set of the powerbi that's\ncalled a financial. So there is valid\n100% data there is no error on it. There\nis no empty cell in this column. If\nthere is empty cell column it will show\nin a form of the percent. Okay. So we\ncan easily understand that how complex\nthe data set and how we uh how many\ncolumns are there in a data set. we need\nto rectify to make it more relevant\noutput in the form of the dashboard.\nOkay. So you can explore it. How many\nerrors are there? No, there is no error.\nOtherwise you need to just do um the\nstandardization or the cleaning the data\nwhich we have already covered in the\nprevious session. Okay. Everything is\nokay. Now and check it. There's a column\ndistribution that is one of the smart\noption. Now by the way uh when you click\non the column distribution it will show\na distribution charts how the data are\ngathered and scattered here. Huh? So you\ncan see that that's behave as like a\noutlier. Okay. And after that the most\nof the values are same. This is the uh\ncount of the values. So in term of the\nstatisticians or data scientists you can\nunderstand that how the data is gathered\nbecause it's a string one. So we don't\ncare about the string one. If there is a\nnumeric value we can easily understand\nthat how the distribution is look like.\nYou can see that and we the scientist\nthe researcher can understand that how\nmany outliers are there in the form of\nthe uh distribution of the data. So\nthat's a smart way to understand the\ndistribution of individual column. The\ncolumn profile is also available there.\nWhen you check it, uh it will show the\nindividual column uh profile which mean\nthat how many data are there? Unique\ndata are there. Okay. Uh you can see\nthat in a country uh in a product okay\nin a discount how many uh unique values\nare there and how many counts are there,\nerrors, empty distant unique values are\nthere. uh empty string are there,\nminimum and maximum values with respect\nto the uh string value or with respect\nto the numeric value are there. So\nthat's all about the understanding of\nthe data. Uh by using this option we can\neasily understand that how complex a\ncolumn is and how uh many step required\nto make it simplify to make a\ninteractive and past kind of the\ndashboard. Okay. Uh next one go to the\ncolumn that's a very simple way. Uh you\nclick on it and by click there are\ndifferent column schema which we uh\nimported the data set in which so if you\nwant to directly move to the sales\ncolumn just click and click okay. So the\nsales column is now selected and you can\njust scroll up and down to uh understand\nthat how is the column is how many\nvalues are there. Okay that's a smart\nway to just move to directly to the\nselected data. The parameters are there.\nIf you want to allow always allow the\nparameter, you can check uh otherwise\nunchecked it. Okay. The parameter we\ndiscussed before what is the parameters?\nNow advanced editor. Uh when you click\non the advanced editor now, so advanced\neditor show a uh one of the M code\nlanguage. Okay. If I just copy, if I\njust copy this data, okay, and I'll just\nopen the notepad. Huh. And just show you\nhow this M code language look like and\nwhat is explaining here. Okay. If I just\nif I just add the data here. Okay, look\nat here. Now you can see that that start\nfrom that start from let okay and in\nkeyword that's the let which mean\nwhatever the assumptions are there and\nin in which we are using here okay by\nthe way it's a comment uh let file shows\nthat the first one source which mean\nthat whatever the data you are importing\nhere it will show that where it's come\nfrom because we are using a financial\ndata own powerbi data so it will show\nthe path where is present okay and after\nthat with extension uh the True. Null\nvalues are there. Financial table is the\nname and its source. Huh? There's a\nsource item. Financial is the name of\nthese file. Which kind of the data is\nthis? It's a table data. Okay. And after\nthat the transform column type. Okay. It\nwill show that how many data types are\nthere. How many columns name are there?\nAnd with respect to the data type. For\nexample, the country. This data type is\ntext, product tax type, discount type,\ntext type. You can see that sales price\nis an integer type. Integer 64 is a type\nof the integer and so on. All the types\nare there. Remember that this uh M code\nsource file which mean that code area\nnormally used to change something with\nrespect to the filtering the data. For\nexample, I can use in future this uh let\nand in form of the data to the filter\nthe rows. Okay, some uh important\nchanging in a raw form of the data. So\nwe must use this kind of the advanced\neditor for the further usage. But right\nnow this is showing that where the data\ncome from and which type of the data are\nthere with respect to the data type are\nhere. Okay. If you want the changes on\nit you need to must understand the amode\nlanguage and after that we will work on\nit to more uh purify the data and we\nwill discuss about the M code language\nin upcoming days. Okay. We are just\nunderstanding the options\nstraightforward first and after that we\nwill going into depth to understand more\nthing about okay it's in touch. Uh I\njust click on the done without no change\nrequired here. And the last option is\nthere is a query dependencies. When you\nclick on it, uh it shows that where is\ndata come from and how many tables are\njoined together. For example, if I just\nimport different number of the tables\nare there. I will show at the last. Um\nso it shows that this is a directory and\nthis is the name of the file. Okay. And\nwhen you click on it, it will just\nhighlight it. You can zoom in and zoom\nout to show up the data. So that is\nquery dependencies. How many tables are\nthere and where what are the different\nresources they come from? because the\npower of PI um handling the 100 plus\nresources uh from the data and they are\njust gathered there and they are\nmultiples resources are gathered and we\ncan use it to make a a dashboard with\nrespect to the type of the data. Okay.\nSo this is all the option we understand\nnow I'm importing the another data sets\nhere to show up the dependencies query\ndependencies in a very historical way\ngood historical way to understand that\nhow this query dependencies work in a\nprofessional way.\nSo I'm importing the another data from\nthe home option\nuh new source excel workbook and in the\ndesktop there is a sales data for fabric\nwe used this data before as well so I'm\njust importing this different number of\nthese sheets are there in this excel\nthat's has a different relationship by\nthe way uh but the problem is that they\nare coming from the one resources okay\nso there are two file which has the two\ndifferent unique resources right now\nokay I Just click okay and after that\nwhen it's imported you can see that\ndifferent number of the sheets are there\npatient table I'm just come to the view\nand just click on the dependencies query\nright now here you can see that huh look\nat this if I just zoom this screen this\nis the first resource that's come from\nthe financial data and there's another\nresource in from there we are just\ngetting the four number of the tables\nfrom there so this query dependencies\nshows that the relationship how many\nresources you are using in your query\nstring or PowerBI. Okay, hope you\nunderstand the concept. We discussed uh\nin this session about a view tab that is\nstart from query setting to query\ndependencies. Hope you understand all\nthe aspect. If you have any query\nregarding the topic, feel free to ask\nand if you like the video, what are you\nwaiting for? Do subscribe the channel to\nunderstand more thing about the PowerBI\nincome in coming days. Okay, stay in\ntouch. See you in the next session.",
  "transcript_chars": 11172,
  "ingested_at": "2026-05-16T04:40:11.202067+00:00",
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    "categories": [
      "Science & Technology"
    ],
    "tags": [
      "Power BI View Tab",
      "Power Query Editor View Tab",
      "Formula Bar in Power BI",
      "Query Settings Power BI",
      "Column quality Power BI",
      "Column distribution Power BI",
      "Column profile Power BI",
      "Power BI data cleaning tips",
      "Power Query View tab tutorial",
      "Power BI 2025 tutorial",
      "How to use View tab in Power BI",
      "Power BI layout view",
      "Power BI column analysis tools",
      "Power BI data transformation",
      "Power BI View tab explained",
      "Power BI full course View tab",
      "#fahadhussain",
      "#powerbi",
      "#powerqueryeditor",
      "PBI"
    ]
  }
}