 very good morning guys, this is Gautam from Kislai Metal. Today we are going to discuss about the pipelines and activities in AguData Factory. Pipelines are nothing but your logical grouping of the activities to perform a task. So, like if I want to either copy the data from one location to another location, I can write a task inside the pipeline. So, the task can be created or it can be executed inside the pipeline. So, pipeline is nothing but your task which you are combining and writing inside the package or something like that. So, activities is nothing but your processing step inside the pipeline. Like if I want to perform a data movement from one location to another location, I can write a copy activity or if I want to delete the data from one location, I can use the delete activity. So, you will perform a task that is a activities. So, activities we have, it takes mainly data movement, data transformation and control code. Data movement is nothing but suppose if I want to move the data from data lake storage to data warehouse, I can use a data movement. Suppose if I want to move the data lake, data from file system to the data lake, I can use the copy activity. So, copy activity is an example for the data movement transformation activities. Transformation, data transformation is like I am extracting the data on top of the data and performing some changes to the data using some scripts, ok. Example is like if I want to extract the data from the data lake and then I have to change the data using some Python script and then again put back the data into the data lake. So, data transformation is like you are extracting the data from your source location and then making the transformation on top of it and then putting it back to the data. So, example we have a lot of data transformation activities in data factory. So, that I will show you in a good photo page. Control code is nothing but it is in a if your data is you are extracting the data and you are putting some if conditions like I want to move the data to this location based on my condition. If it is true, then move to this location. If it is false, then move to other location. So, this kind of activity which we will handle in the control code, ok. So, conditional based expression control we can handle it in the control code. To move more about this activities on pipeline, we can very well use it to the data factory link which I have listed in the. Let me walk through the pipeline and activities in the Azure Data Factory page. If you see here my screen Azure Data Factory. So, if you click on this plus button it will allow you to create a pipeline, ok. This is a pipeline which is created now. Now, on the left side we will find various activities like if I want to move the data from one location to another location I can install copy activity, ok. So, here you have this way the source and sync location, ok. And then if you want to create any mapping beneath the source and sync location, we can import the schema and do it, ok. And similarly we have the delete actually, delete is nothing but your source location where you want to delete it. So, each and every activity which we need is a data set. Data set is nothing but you are referring the actual data present in the location and then you are consuming the data and producing the new data, ok. So, data set is very very mandatory for consuming it and producing the new data within activity. So, every activity will have a data set, ok. Where if we want to get the data from a file such as present in your local machine or if you want to get the data from this area does not put. So, you have it you must have a data set, ok. This is these two are the examples of the data movement transformation, the data movement activity, ok. So, transformation is like we have observed function here, we have bad service data bridge. So, these and all comes under transformation and control flow we have these conditions. If the case is true will then we will we have the execute another activity which works means we have execute another activity. So, we have similarly like switch actually, ok. We will discuss about each and every activity in the next sub communication, ok. The default case you can write it, other way is you have to write a different case. So, this is activity actually, we will discuss about the limited services and data sets which are on other types of activity in the next upcoming videos. So, hope you enjoy it. Please subscribe. Thank you.