What is at the core of every Business Intelligence, Data Science, and Machine Learning project?
You need data to understand what has happened in the past, to predict what may happen in the future, to discover patterns and anomalies, and to gain the insight necessary for making faster and better decisions.
But before you can do any of those things, you need to collect, store, transform, integrate, and prepare your data. Azure Data Factory (ADF) is a service that enables you to quickly and efficiently create automated data pipelines – without having to write any code!
In this session, we will go through the fundamentals of Azure Data Factory and see how easy it is to build solutions that can work with all your data on-premises and in the cloud. We will explore some key features such as Mapping Data Flows for visual data transformations and Wrangling Data Flows for visual data preparation, as well as how to schedule and orchestrate your finished data pipelines. Throughout the session, we will discuss different use cases and scenarios, as well as when and why you should use Azure Data Factory for your projects.