Power BI has two main types of data connectivity: Import (copying data into Power BI) and DirectQuery (querying data directly from the source), along with Live Connection (to specific Power BI and Analysis Services datasets) and Composite Models, which combine these approaches. Choosing the right connection type depends on factors like data volume, the need for real-time data, data modeling capabilities, and report performance.
Here's a breakdown of each connection type:
1. Import Mode
- How it works: Data is copied and stored directly within the Power BI report, allowing for efficient data model creation and transformations using Power Query.
- Pros: Fast query performance, comprehensive Power Query transformation capabilities, and full access to data modeling.
- Cons: Requires scheduled refresh for data to be updated, can consume significant storage, and may not be suitable for very large datasets.
- Best for: Most scenarios where data doesn't need to be completely real-time and a manageable amount of data is involved.
2. DirectQuery Mode
- How it works: Power BI sends queries directly to the external data source to retrieve data in real-time.
- Pros: Supports large datasets, provides near real-time data, and requires less storage in Power BI.
- Cons: Performance depends on the source database, Power Query transformations are limited, and data modeling capabilities are restricted.
- Best for: Situations requiring near real-time data or when dealing with massive datasets that cannot be imported.
3. Live Connection Mode
- How it works: Creates a live connection to a specific Power BI dataset or Analysis Services tabular model, without importing data into Power BI Desktop.
- Pros: Leverages existing, complex models and DAX measures created in the source, and supports large data models.
- Cons: No access to Power Query for data transformation, and report performance is dependent on the underlying Analysis Services model.
- Best for: Connecting to established, robust data models in Power BI or Analysis Services, allowing for consistent data and logic across multiple reports.
- How it works: A hybrid approach that allows you to combine data from different connection modes (Import, DirectQuery, and Live Connection) within a single data model.
- Pros: Offers a flexible way to combine the benefits of different connection types.
- Cons: Can introduce complexity and requires careful consideration of model design to ensure performance.
- Best for: Scenarios where you need to integrate data from both real-time sources (DirectQuery) and static datasets (Import) in one model.
5. DirectLake (Newer Mode)
- How it works: An optimization for Azure Synapse Analytics and Fabric, it allows DirectQuery to read directly from the underlying data in the data lake, offering high performance with large volumes of data.
- Pros: Improved performance for large datasets with near real-time data.
- Cons: Limited to specific data sources and platforms.
- Best for: Large-scale data warehousing and analytics scenarios, leveraging the data lake for speed.