 Hello, welcome to SSUNITEX, so say this side and today we are going to see about the CASA lookup. So in the last video we have seen about the CASA sync and the CASA dataset. So if you haven't watched the last video of this video series, so I strongly recommend to watch that video before going forward because all these videos are in sequence, so it would great if you can watch in sequence. So what is CASA lookup? So a CASA lookup allows you to do an inline lookup of the output of the CASA sync. There are two functions available to use on each sync, lookup and outputs. So these two functions can be used. For the output we have already used in the last video. In this video we are going to use the lookup function. So let me go in the browser and we will try to understand the requirement. So our requirement is we want to send the data into some customer and here we have the data like sales order ID, sales order date, customer ID, quantity, value and country. But customer ID value is not as much clear for that person. So what we have to do, we have to add the customer name as well. And the customer name information is available on the Azure Blob Storage in one of the files that is the customer details.cfc file. So what we are required to do, we need to do the lookup based on the customer ID from this location that is database to the Azure Blob Storage and after that we will be sending that file. And that file will be loading into the output folder of the Azure Blob Storage. So first what we need to do, we need to keep this customer details.cfc file as a sync in the output of the Dataflow and after that from there we will be going to use with the source. So let me go into the Azure Data Factory and here let me try to add a new Dataflow and this Dataflow let me call like Dataflow cache lookup. Now as I told you first we are required to put the customer file into the sync and the sync that will be the cache sync. So let me try to add the source as we have already created the dataset for the source. So we need to select that that is dataset customer. Let me try to open and verify. So here it is referring the input folder and here the customer details.cfc file. Similarly we can also see customer.cfc file under this input folder. Let me go into the data preview and try to refresh. So we will see all the data which is available in this table. In between let me try to add a sync and that sync will be your cache sync. So as we could see we have all the data here. So we want to keep this data into the sync as cache spark. So here we can see the cache. So let me try to select this cache. Once we have selected the cache then other options which were displaying below has been disappeared. Now let me go in the setting. So in the settings we are required to select the list of columns or the custom expression. So this is the key column by which we want to do the lookup. So in our case that column is the customer ID that we have seen here. So let me try to go and select the customer ID here. So we can click and select the customer ID. Now we can go into the data preview and try to refresh. So we will see all the data. So now data should be here inside the cache sync. So as we can see now we will do the actual requirement get the data from this database and loading into the output folder of the zero blob stories. So let me add the source for this. We have already created the data set. So we have to select that one. Let me go into the data preview and try to refresh. So we will see the data. So here as we could see we have all this data. Now let me try to click on this plus symbol and next what we need to do we are required to add one more column and that column will be the customer name. So we have to use the derived column transformation. So under this derived column transformation here we are required to add a new column and that column is the customer name. So we have to select this customer name. Now here under this expression let me try to click on this. So here we need to write the expression to get the customer name. So for that first we need to get it by using the customer ID from the cache sync. So here we can see the cache look up under this expression elements. So let me select this here the sync one we can select. Remember in the last video we have used the outputs but here we are getting the value by using the lookup. So we have to use the lookup and lookup is the based on the customer ID. So we can use the customer ID. Now let me try to refresh. So we will see the data of this. So here as we could see we are getting the data but before that we are getting this another column and this column is indicating the value for the customer ID. So we don't want to keep this value we just want to get the second column which is the customer name. So we have to use the dot and after that let me use the customer name. Now let me try to refresh this. So this time we will be going to get only the customer names that you can see here. This time we have only a single column and the value which is the customer names only. Now let me try to save and finish. So we have done with the lookup of this. Let me try to put this into the output folder of the sync location. So here we did not created the data set. So let me try to use the inline instead of the actual physical data set. The type we want to keep this as in delimited text file. Here let me select the link service and after that let me go into the setting and here let me try to select the path by which we want to keep the file. So that is the output path. Let me click on OK. First row as header and the file name we want to keep the file name as sales by customer dot CSV. Go to the data preview and try to refresh. So we will see the data. So this data will be going to load into the output folder. So any person can access the data. As we can see here we have the customer names as well. Let me try to publish this. So here the problem like we need to select if you have remember we have to go into the optimize and need to select the single partition. Now let me try to publish this again and in between let me go and try to add a new pipeline to execute this data flow. So here we have to use the data flow activity. So publish is completed. So let me try to use that data flow. So which is the data flow lookup that is a case one. Now let me try to debug it. So go to the output folder and in the output folder here we can see the file. So let me try to open and we will verify the data as well. So this file will be having all the data from the SQL table and the last column that the customer name we can see. So we have used this by using the case lookup. So I hope guys you have the better understanding on the case sync and the case lookup. Thank you so much for watching this video. See you in the next video.