 Hello, welcome to SSUNITEX, we shall decide and today we are going to see about the select transformation in SEO data factory. So what is select transformation? So before going to discuss about the select transformation, if you haven't watched the lookup transformation video in this video series, so I would strongly recommend to watch that video. So what is select transformation? So to use the select transformation to rename drop or reorder columns, this transformation does not alter the row data. So basically this transformation can be used to rename drop or reorder the columns and this transformation is not going to use to alter the data but we can choose which column are rock gated downstream. So this is basically we can say that this transformation is going to play with your columns not with the data. In select transformation, user can specify fixed mapping, use pattern to do rule based mapping, to enable auto mapping, fixed and rule based mapping can both be used within the same select transformation. If a column does not match one of the defined mapping, it will be dropped. So that we will see in the practical don't worry for now if that is not understood. So go to on the browser and here first of all here we can see the employee file and the payroll file. In the earlier videos, we were doing the lookup between these two and whatever the output we were getting, we want to put that into the output folder. But if we are going to use the lookup transformation, then whatever the columns are available at the source and at the lookup, all those will be available in the destination. But we don't want to keep the duplicate columns there because employee ID is common between these two and employee ID will be coming twice in the lookup transformation. So go and try to see that in the practical. Here let me try to add a new data flow and under this here we can see the add source. So in this add source, the data set that we have already created this employee source input after that need to add another source and this source is for the payroll data. So we can select the payroll data set here. Now here we can click on this plus symbol and here we can see the lookup transmission. So we can add that one. Now under the lookup transformation, the primary stream that we have already selected source one, the lookup stream which is the payroll one that will be your secondary. So we can select the source to here. Now here we can see the match multiple rows that we have already discussed in the lookup transformation. Here I am going to add the conditions. So on the basis of employee ID, I just want to do the lookup. Now here everything looks okay. Now we can see the output of this lookup. So go to the data preview and try to refresh it. So here as we can see it is having the employee ID twice. So one is coming from the source and second is coming from the lookup. So we don't want to keep twice. So let me click on this plus symbol and we need to add the select transformation here. So under the select transformation, we can closely observe this input columns. So auto mapping option is here. So let me try to on this auto mapping. So all inputs mapped by name including drifting columns. So it will be going to map automatically. Now if we want to do the mapping at our end, then we can also do that. So how we can do that? So first let me try to remove the duplicate columns like the employee ID from the source to we don't want to keep. So we can remove that and after that we can also rename this. So like here we can see the employee address. So let me have the employee address the complete name. So we can rename the output column names and after that we can also rearrange the column sequence. So like salary amount we want to keep after the employee name. So we can just put it here. So these options we can do directly. Now here we can see the add mapping. So we can click on the add mapping. So it is saying the fixed mapping. Let me click on that. So here what will be the output column of this. So as we can see all these columns, so inside the mapping we can select any one of this column and we can provide the name of that. So let me try to remove this. So this is for the fixed mapping in the rule based mapping we can click on that and here we can add the matching condition and here we can add the output column name by using expression. So that we can also do that. So I am not going to do all these here. Let me delete it. So mapping is succeed. Now we can go in the data preview and try to refresh it. So this time your employee ID will be having only ones and your salary column should be switched. So as we can see employee ID is coming once and salary column is here. So that we can see and we can also verify the address column. So this should be having employee address complete. So this is the use of selected statement. Let me put this in the destination so that will be the sync. So we can add the sync here and inside the sync let me add the inline and here let me select the delimited text as in output and we can select this SSU testing link service. Go to the settings and try to select the folder path. So under the folder path we can go in the output. So this will be the folder from where we want to keep the file and here we can see the option for the first name first row as header. So we can select that one as well. Now we can publish it. Now we can publish. So it will be published. So we can see the published completed. Everything is okay. We can go here in the pipeline and try to add a new pipeline and this pipeline we want to execute the data flow that we have created. So we need to ask the data flow activity here go to the settings and under the settings we can see the data flow of the data flow one that we have created. Now we can try to debug it. So it will be going to load the data into the output folder. So that is in progress we can see that go to the output folder here. Here we can see these files. So it is completed and here we can see all these files. So now let me try to open one of these files and here we can see all the data. So that the first column is the employee ID employee name then the salary amount and after that the employee address the complete name here in the column header. So this is whatever we have seen there. So thank you so much for watching this video. I hope you have understood about the select transformation. See you in the next video.