While most data analysts are still developing reports in Power BI Desktop, more and more want to use the Power BI service for this purpose. Maybe it’s because they’re using a Mac computer, a Linux operating system, or for some other reason. That is why the Microsoft development team made it possible for users to access the Data Model directly from the web browser, i.e. now you can use Model View at the same way as in Power BI Desktop.
A data warehouse is a centralized system used to store, integrate, and organize large amounts of data, often from a variety of sources, in order to prepare it for reporting and analysis. Microsoft Fabric offers users to easily create data warehouses within organizational tenant environment from which you can create reports directly in the Power BI service or by using the Power BI Desktop application.
Objects (data sources) within the Microsoft Fabric organizational environment can be easily leveraged in the Power BI Desktop application to create reports. These can be: Lakehouse, Warehouse, Datamarts (segments of the data warehouse, grouped by functional units, suitable for reporting), SQL Databases, KQL Databases… In this article, you will learn how to use Lakehouse tables to create reports.
Lakehouse is a unique architecture that incorporates the best features of a Data Lake repository, which is used to store unstructured and semi-structured data, and data warehouses, which are used to store structured tables used to create reports. That is, you can store all this data in one place and access it via PySpark or SQL language…
Dataflow is a tool that has been around in the Power BI service for a very long time , and is used to import, transform, and load data into a semantic model (ETL). Practically, it is Power Query in a cloud environment. With the advent of Microsoft Fabric, Dataflow Gen2 was introduced , which is much more advanced compared to the previous version and enables faster work with large amounts of data, as well as their parallel processing.