{
  "video_id": "FK6pohCxtGE",
  "channel_slug": "fahadhussaintutorial",
  "channel_handle": "fahadhussaintutorial",
  "title": "Lesson 13: Power BI Merge Queries Explained | All Join Types in Power BI with Real-Life Examples",
  "duration_seconds": 618.0,
  "url": "https://www.youtube.com/watch?v=FK6pohCxtGE",
  "upload_date": "",
  "transcript": "Hi, welcome back again. Uh in this\nsession we focus on to understand the\nmerge queries in power query editor. Uh\nso based on this I just imported uh two\ndata set here. Uh one file in which\nthere are two uh sheets in Excel\ncustomer and order and another one is\ncalled the same university data as usual\nwe are uh doing for the practice and\nunderstanding the options on it. So to\ndo before I just introduce this base and\nimportant thing whatever we discuss and\nwhatever we discuss in future all the\nthings are available on my YouTube\nchannel. Come to the YouTube search me\nby the name of fatherus and cs. This is\nmy channel playlist in which there are\nthousand plus videos are there with\nthese you can watch and the material\nthey are used in the uh video session\navailable on the my blog fathers\nbloggerspot.com you can download it. So\nif you didn't subscribe the channel what\nare you waiting for? to subscribe the\nchannel to get familiar about that what\nis going on in the technology world.\nOkay. So first I just show you the data.\nOkay. This is the two data I'm just show\nyou. Uh we are using here for the merge\nqueries. This is the original one by the\nway. Uh this is the base thing the\ncustomer. Okay. I'm just zoom it. This\nis a customer data in which the customer\nID, customer name and country. The\nanother one is the order. So in the\norder you can see that the customer ID\nis going to pass here. Huh? the customer\nid is going to pass here from the\ncustomer. So I can say that this id is\ngoing to pass in the order one and there\nis a relationship between these two\ntable that's called a base relationship.\nOkay. So uh after that I just go to the\ntransform data option and this power\nquery option will be open from this.\nOkay. And here you can see that all the\ntables are there. So the first one is\nthe customer the base table and the\norder the another table. Okay. Just\nignore the rest of the things which we\nused in the previous session by the way.\nSo if I just uh make it proper now. So\nhere you can see that table is proper.\nWhat about the order order is also\nproper. Okay. So when you click on the\nmerge query so it will show this option\nin which whatever the table you have\nselected it will show on the base one.\nOkay. Otherwise uh you need to change\nit. So I'm just click on the customer\nand click on the first option merge\nqueries and from the second table where\nI need to create a relation. So I need\nto click on the order one. So the\ncustomer will going to make a relation\nwith the order and which uh column is\ngoing to use as a base for the relation.\nCustomer ID from the customer and\ncustomer ID from the order. And you can\nsee that when the relationship are\nright, it will show the check sign here.\nRemember that. Now the base another\nthing is very important. How many type\nof the joints are there? Joints. Okay.\nLeft, right, outer, inner, left, anti,\nright ent. I will show you one image and\nafter that come here to understand how\nthis option work.\nRight. So there are six number of the\njoints that support PowerBI. The first\none is a left outer join. Okay, that's a\nname left outer join. What does it mean?\nWhich mean that if there is a two table\nand we are going to apply our joints on\nthe PowerBI. So all the values that are\nmatched both of them. This is the area\nmatch part. Okay, I'm just going to zoom\nit match part. Not only the match part\nalso the unmatched part from the left\npart which mean complete table of the\nleft including the match one will be the\nresult of this one for example this is a\ncustomer table okay and this one is the\norder table okay which I'm going to use\nso if it's going to left outer join the\nall the values of the customer will be\nthere including the match one but\nremember that from the outer uh values\nfrom the right hand side the order table\nif the values are not matching which\nwill not be the part of my original\nresult of let outer. Okay, that's cool.\nNow the next one is the right outer.\nSame definition but in a reverse order\nwhich mean that the matching part which\nare matched in a both table but rest of\nthe parts from the right part as well\nwhich mean that order if I just write a\norder table here. Okay, all values of\nthe order including the match part but\nnot from the customer. Okay, that will\nbe the result of the right outer part.\nWhat about the full one? The full one by\nthe name is suggest you all the data\nfrom the both table including the\nmatching and unmatching as well and you\ncan see that all the rows from the both\nmatching and not matching the table.\nOkay. The fourth one inner as the name\nsuggest here inner which mean that only\nthe match part not from the not matching\npart from the left and not matching part\nfrom the right. Okay. Only the matching\npart will be written. Left anti- join.\nWhat does it mean? Uh the left outer\njoint and the left anti- join.\nDifference is that left part complete\ntable just ignoring the matching one and\nthe right one. Okay, which mean that\nnone of the values has come from the uh\nright part either is a matching or not\nmatching only the left table will be the\nresult. Okay, not this one. Huh? Not\nmatching one. And the last one is a\nright entity which means that right\ntable only not a matching not a left one\nthat will be the result. So there are\nsix number of the joints in PowerBI.\nLeft outer, right outer, left entity,\nright entity, full outer and the inner\none. Let's explore this in the PowerBI.\nSo I just uh selected the both option uh\ncustomer ID from here and there. And\nafter that you can see that there are\nsame type of these one left outer which\nmean that left outer which mean all from\nfirst matching from second which mean\nthat all from the first including the\nmatching one that's called a left outer\njoin. Now after that there is a option\nuse fuzzy matching to perform the merge.\nThat is a very important concept in\nPowerBI. What's the meaning? Look at\nfuzzy matching allow PowerBI to match\nraw even it's the value are not exactly\nthe same but are similar. For example,\nwhen you are applying the matching\nproperties between two tables. So it\nwill finding the exact same value. But\nif you mark the fuzzy u allowing\nmatching option it will if the value are\nsimilar okay not exactly the same it\nwill also depart. So it is useful when\ndata are misspelling. Okay. Extra spaced\ndifferent format or slightly different\ntext like John is Smith uh written in\nthe form of the J O N Smith or ABC uh\nlimited is right ABC limited complete\nword. So if there is a complexity are\nthere in your data set. So you can just\ncheck the fuzzy matching to uh conclude\nthe best matching result after applying\nthis option. Okay. So if if it's all\nabout your understanding of your data.\nOkay. After that the last one the\nselection match five row of five which\nmean that based on this data five number\nof the values are matching. Okay if I\njust click okay. Okay look at that. So\nthe first option left outer. I just\nclick on it. Look at this. The result is\nmatched here. And after that one of the\ntable uh is uh column is added with the\norder. What does it mean? The customer\nis the left part and the order is the\nright part. So which mean that if I just\nclick on this table now it will make a\nrelation with C01. Okay. how many times\nC01 is going to repeat in the order uh\ntable. Okay, when I just click it, it\nwill show me the result. Okay, it it\nwill show me the complete result. Look\nat this order custom. It will matching\nthe all values and the other part is\nalso there. Which mean that complete\nresult including the matching one is\nalso the result. You can easily compare\nwith the original table. If you just\ncompare this one from the original\ntable, so you can easily understand this\nthing. Right? There's the first result.\nI just make it cancel this one. Make it\ncancel this one as well. Uh customer ID\nremain. If I just click merge queries\nagain, this one is the next option.\nWrite outer. Okay. All from the second\nmatching from the first. Which mean that\nsecond table will the result all\nincluding the matching one. Huh. Use\nfuzzy. Yep. And after that, oh sorry,\nthe order one, the customer ID here,\ncustomer ID here, right outer. Click\nokay. Look at this. The right outer.\nWhen you click any option, it will show\nthe complete result from the left to\nright choice. Okay. It's all about the\nunderstanding of the data. How many\ncomplex data do you have? So you can\nobserve the difference on it. Okay. If I\njust took a very sample basic data to\nmake you understand the concept.\nSimilarly bucket uh if I just click on\nthe customer again the first option uh\norder customer ID there and here and\nthere is a third one full outer join\neither is a matching not matching or\nwill be the result. So I'm just make it\nclick okay. All the result will be\nthere. There is no difference on it. I\njust click on the\nC004. Complete table result is there.\nOrder ID, customer ID there and the\ncomplete table of the result as well.\nSimilarly back to the option this is the\ninner not matching rows only matching\nrows. Okay, inner joint. So only the\nmatching one. This is a smart thing by\nthe way. So how many option are matching\nhere? You can see that 1 2 3 6 5 one\nmatching which mean that four and five\nare not matching. Remember I just click\non it. You can see that four and five is\nnot here. Why? Because it's not matching\nwith one. Okay, I'm not talking about\nthis one. I'm talking about this thing.\nSo, it will matching dissolve only\nthere. I just back\nit. Similarly, I just click on the order\nID. There is a left entity.\nOkay. Click on this one. This one option\nselect. And same for the right one.\nThere is no left entry. That's why table\nis empty blank. Why? You can see that\nonly the left part and the right part\nbutton\nover. So I'm just click it\nagain cancel and the last option is also\nthere. So the customer ID from the\norder okay and the last option is right\nent are there because the table is empty\nbecause not left entity are enabled on\nthis data set. So hope you understand\nthe concept of the uh joins uh which\nmean the merge queries. Remember that\nthis is the first option and there is\nthe second one is same but every time\nwhen you click on the second option to\ncreate it will make a duplicate result\nin the original table it will not\ndisturbed. Okay by the way all the same\nthings are there in the second option.\nSo that's all about the merge queries uh\nusing a dummy data set to understand the\nconcept how the merge queries work and\nhow many types of the joints are there.\nwe discuss if there is any complexity\nand any troubles are there feel free to\nwrite a comment I will try my level best\nto write reply you on this uh if you\ndidn't subscribe the channel do\nsubscribe to motivate me to do such kind\nof the things for you all the time okay\nuh see you on the next session to\ndiscuss about the uh other tabs option\nuh according to the power query editor\nF.F.",
  "transcript_chars": 10856,
  "ingested_at": "2026-05-16T04:40:34.908257+00:00",
  "source": "channel",
  "yt_meta": {
    "view_count": 135,
    "like_count": 3,
    "channel_id": "UCapJpINJKHzflWwCQ8Kse2g",
    "categories": [
      "Science & Technology"
    ],
    "tags": [
      "Inner join in Power BI",
      "Left join in Power BI",
      "Right join in Power BI",
      "Full outer join Power BI",
      "Power BI anti join",
      "Power BI data modeling tutorial",
      "How to merge tables in Power BI",
      "Combine data in Power BI",
      "Power BI real-life examples",
      "Power BI beginner tutorial",
      "Power BI relationships vs merge",
      "Power BI data transformation",
      "Power Query merge vs append",
      "Learn Power BI step by step",
      "Power BI merge queries with examples",
      "Power BI best practices for joins",
      "fahad hussain",
      "#fahad"
    ]
  }
}