A pipeline allows you to manage activities as a set instead of each one individually. For example, you can deploy, schedule, suspend, and resume a pipeline, instead of dealing with activities in the pipeline independently.+
Data Factory supports two types of activities: data movement activities and data transformation activities. Each activity can have zero or more input datasets and produce one or more output datasets.+
An input dataset represents the input for an activity in the pipeline and an output dataset represents the output for the activity. Datasets identify data within different data stores, such as tables, files, folders, and documents. After you create a dataset, you can use it with activities in a pipeline. For example, a dataset can be an input/output dataset of a Copy Activity or an HDInsightHive Activity.
You can view more information at the following page https://docs.microsoft.com/en-us/azure/data-factory/data-factory-create-pipelines