In the world of Microsoft Power BI, data is the foundation of meaningful insights and informed decision making. However, managing and preparing data for analysis can be a complex and time-consuming process. This is where dataflows can help. In this video, you will explore what dataflows are and why they are used in Power BI. You'll learn the subscription level required to use them and engage with a fictional scenario showcasing their application and the advantages and limitations they offer. Adventure Works is accompany operating in multiple regions each with its own set of data sources and reporting requirements. To manage these multiple data sources, Adventure Works wants to use the Power BI dataflows feature. Dataflows allow you to connect to data sources, perform data transformations, and create business logic to build data entities that can be shared across different reports and dashboards. They can also be published to the Power BI service and in shared reports and dashboards. Dataflows simplify the process of data preparation, allowing users to cleanse, transform, and shape their data with ease. You can apply business rules, clean untidy data and create calculated columns through Microsoft Power Query, a powerful data transformation tool within Power BI. Dataflows offer a visual interface for building data transformation logic making it accessible to users lacking coding skills. You can use dataflows and Microsoft Power BI Desktop and Microsoft Power BI service. In Power BI Desktop, you can create and manage dataflows using the Power Query Editor. This allows you to connect to various data sources, perform transformations and define the structure of your data entities. You can then publish these dataflows to the Power BI service for further use. Once published to the Power BI service, dataflows can be accessed and managed through the Power BI web interface. You can schedule dataflow refreshes, configure data connectors, and establish relationships between dataflows and other datasets in your workspace. Additionally, you can use the capabilities of Power Query Online, a cloud-based version of Power Query to perform data transformations directly in the Power BI service. By supporting dataflows in both Power BI Desktop and Power BI service, Power BI enables a seamless experience for users to create, share, and collaborate on dataflows throughout the entire data preparation and analysis process. This flexibility allows users to work with dataflows using their preferred environment while ensuring consistent and efficient data management across both desktop and cloud-based environments. A Power BI Pro license is required to use dataflows and Power BI. However, a Power BI premium subscription is necessary for advanced features and capabilities such as incremental refresh, compute engine selection, and larger data capacity. Power BI Premium unlocks additional functionalities and performance optimizations that enhance the dataflow experience. Advantages of dataflows include reusability. Dataflows enable the reuse of query logic and transformations, saving time and effort in data preparation tasks. Data centralization: Dataflows provide a centralized and consistent data source ensuring data integrity and reducing duplication. Collaboration: Users can collaborate on dataflows, making, sharing and working on data preparation processes easier. Scalability: Dataflows use cloud-based processing capabilities enabling efficient handling of large data sets and complex transformations. Limitations of dataflows include data refresh. Dataflows have specific refresh limitations such as the frequency and dependencies on data source availability. Dataflow management. Currently, dataflows are managed individually and there's limited visibility into dependencies between dataflows. Advanced transformations: While dataflows offer a wide range of transformations, certain complex scenarios may require advanced coding or alternative solutions. Dataflows in Power BI help users streamline and enhance their self-service data preparation workflows. By providing a scalable and collaborative approach to data integration and transformation, dataflows enable organizations to unlock the true potential of their data. While dataflows offer numerous advantages such as: reusability, centralization, collaboration and scalability, you must be aware of their limitations and consider alternative approaches for advanced transformations. By effectively using dataflows, you can accelerate data preparation, ensure data consistency and make informed decisions based on reliable and well-prepared data.