The gross world national product has been hovering around 3.5 percent for the last decade. Therefore, many companies are trying to derive new business from the current data that they have. How can a company consolidate data in one central place to allow for data exploration and business intelligence? The solution to this problem is to design a modern data platform. In this talk, I will be talking about two A.D.F. design patterns that can be used to achieve this goal. You will learn about how to combine components like Azure Data Lake Storage, Azure Data Lake Analytics, Azure Data Factory, Azure SQL server, Azure Analysis Services, Machine Learning and Power BI into an architecture that meets your company’s needs. Of course, we will go over how to use nomenclature to keep track of source systems and lineage within your data lake. We do not want any data swamps! At the end of the session you will have a good understanding on how linked services, data sets, pipelines and triggers play a role in Azure Data Factory.