In short, Dataflows integrates data lake and ETL technology directly into Power BI, so anyone with Power Query skills (yes – Power Query is now part of Power BI service and not just Power BI Desktop and is called Power Query online) can create, customize and manage data within their Power BI experience (think of it as self-service data prep). Dataflows include a standard schema, called the Common Data Model (CDM), that contains the most common business entities across the major functions such as marketing, sales, service, finance, along with connectors that ingest data from the most common sources into these schemas. This greatly simplifies modeling and integration challenges (it prevents multiple metadata/definition on the same data). You can also extend the CDM by creating custom entities. Lastly – Microsoft and their partners will be shipping out-of-the-box applications that run on Power BI that populate data in the Common Data Model and deliver insights through Power BI.
A dataflow is not just the data itself, but also logic on how the data is manipulated. Dataflows belong to the Data Warehouse/Mart/Lake family. Its main job is to aggregate, cleanse, transform, integrate and harmonize data from a large and growing set of supported on-premises and cloud-based data sources including Dynamics 365, Salesforce, Azure SQL Database, Excel, SharePoint. Dataflows hold a collection of data-lake stored entities (i.e. tables) which are stored in internal Power BI Common Data Model compliant folders in Azure Data Lake Storage Gen2.
Also check out the comments for some clarification on why you’d want to use Dataflows rather than doing the work directly in the data lake.