 Hey guys, welcome to SSUnitech. This is part 1 of the ADF Tutorial. Today we are going to discuss about the introduction part of the ADF. In this video series, we will be going to see in the details step by step all the concepts inside the ADF. Before going forward, if you haven't watched the video tutorial, then I would strongly recommend to watch all those videos. For that, you can go on the browser and search for SSUnitech. After that, you can go in the channel. Then you can go inside the playlist. Inside the playlist, you will see the playlist for the ADF Tutorial. You can watch all the videos. Here you can understand what is ADF and what are the different things you can understand over here. Let's get started with today's video. What is ADF? ADF is the SEO data factory. ADF is the SEO Cloud ETL service. This is very similar to the SSIS. SSIS is on-prem ETL tool. This is SEO Cloud ETL service. This is to scale out the serverless data integration and data transformation. It offers a code-free UI for intuitive authorizing and single pane of glass monitoring and management. You can also lift and shift existing SSIS packages to the server and run them with fully compatibility in ADF. If you are having your existing SSIS packages, we can directly use those packages inside the ADF. That we will see in the upcoming videos. Next is the SSIS integration. Runtime offers a fully managed service. You don't need to worry about the infrastructure management. Here you can create the pipelines. Pipelines are very similar to the SSIS packages. Here we can create the pipelines. Under that pipeline, we can do the ETL operations. ADF is a cloud-based ETL tool. E for the extract, T for the transform and L for the load. Here we can extract the data from different sources. After that, we can do the transformation on that data to make meaningful data. After that, we can load that data into any destination. This is the ETL tool for the cloud. SSIS is the tool for the on-prem environment. Here you can understand how flows are going in the industries. First, you can see the data sources. The data source that could be in the on-prem network or it might be on the external data. That could be the binary data or the Cosmos data. That will be the NoSQL data. Then we are having this data factory. Inside the data factory, we can consume that data from the on-prem networks or the external data that could be the Cosmos script or the cloud data. We are going to store that inside the store blob. We have already discussed about the storage blob in the Azure tutorial playlist. You can watch that and understand about the store blob. After that, you can see the SQL data warehouse. Again, we have already discussed in the Azure tutorial part. You can watch there. First, we can get all this data. After that, inside the data factory, we can load that data inside the SQL data warehouse. After that, now data is available in the data warehouse. Next, we can use any analysis services. After that, we can represent that data inside the visualization. For the visualization, nowadays, we are going to use Power BI, which is a very powerful tool for Microsoft. Next, about the Azure Data Factory versus SSIS. As I told you, Azure Data Factory and SSIS both are the ETL tool. Azure Data Factory is the ETL tool for the cloud. SSIS is the ETL tool for the on-prem environments. If your data is available on your local system or local Excel file, then you can use the SSIS packages. If your data is available on the cloud or that scenario, you can use the Azure Data Factory. Azure Data Factory is much more powerful because it can be integrated with your on-prem environments as well. Azure Data Factory has the facility to interact with your on-prem environment as well as with the cloud environment. Thank you so much for watching this video. I hope you have the better understanding about the area. In the next video, we will be going to see India Knowledge. See you in the next video.