 Hey guys welcome to SSU DTECH and this is Susheel. So this is continuation of Power BI Tutorial and this is part 5 of Power BI Tutorial. So today we will start with the query editor. So what is query editor and where we can use it. We will discuss in this session. So after watching this video you will understand about the data modeling. How we can prepare the data for the visualizations which is available in the Power BI. So as I told you in the earlier this is very powerful tool. Once you will see all these videos you will be able to understand about the visualizations. How we can create it and how we can prepare the data. So let's start with the query editor. So what is query editor? So basically this is an editor where we can prepare the data for the visualizations. So first we will get the raw data and after doing certain transformation on the raw data we will get the final data. And by using that final data we will prepare the visualizations. So these transformations can be done inside the query editor. So let's have a look of the query editor. So first just open the Power BI desktop. So it will take few seconds. So on that time let's have a look of files. So here we have three files Australia, UK and US. So we are having the sale of these countries. So as we can see we are having sale order ID, then order date, then due date, sale order number, then customer ID, account number, sale person, then bill to address ID and many more columns those are required. So as we can see here we are having the address and postal code, country and many more columns. And second we are having the same metadata on this UK. So it is having the sale of UK and in the US we are having the sale of US. So we are having total three files. So go to our Power BI and don't try free just close it. So here as we can see we are having in home ribbon and inside this we are having the get data. So we can get the data from different sources. So we are having the flat file with the comma delimited. So we can use the text or CSV. So just click on this. And let me select the Australia first. So click on open. It will take few seconds. So delimited is comma that looks good. We are having all the columns and with all the data. So that is good. Here we are having two options. First we can load the data direct to the Power BI desktop or we can use the transform data. So inside the transform data it will open the query editor where we can prepare the data. So just click on this transform data. So we can click on this. So here as we can see it is open power query editor. So inside the power query editor we will prepare the data. So this is the query editor that is I'm talking about. So here we are getting the option to get the data from this query editor directly. So as we can see in the new source we can use the text or CSV. This time for UK and delimited is comma that looks good. We can click on open. So here we can see we are having the queries. So inside the queries we are having this Australia and UK. Now let me get the data for US as well. So one more time text or CSV then US and click on open. It will take few seconds and that will be loaded inside the query editor. Click on OK and it is US. So we are having three files. First for the Australia second for the UK and then we are having this file for US. So here we are having these files but as we can see we don't have the proper data. So we will do the certain transformations on this and we will prepare the final output and by using that output we will create the visualizations. So in the upcoming videos you will see how we can play around this query editor and how we can prepare the data. So that's it for this video. In the next video we will see how we can edit the rows and how we can play with the rows. So I hope guys you have understand about the query editor and how we can edit the queries inside the query editor. So thank you so much for watching this video. In the next video you will see how we can edit the rows in the query editor. So if you like this video please subscribe my channel, and please share it with your friends. And thank you so much for watching this video.