SQLBits 2024
Point-in-time analysis in Power BI and Fabric
In this session, we will explore various methods for tracking data history, so that you can provide your users with the ability to answer questions about how your data has changed over time.
We are not time-travelers, so if you want to know what data looked like at a specific point in time, or how it evolved over time, you need to prepare for it by implementing point-in-time capabilities into your Business Intelligence.
In this session, we will explore various methods for tracking data history, so that you can provide your users with the ability to answer questions about how your data has changed over time. We will start by looking at some of the methods that can be used to track data history, such as snapshot tables and slowly changing dimensions. Then, we will explore how to implement these methods in Microsoft Fabric.
Topics:
- Point-in-time analysis
- Mutable vs. immutable data and stragies
- Incremental (Delta) loads
- Change data tracking
- Slowly Changing Dimensions
- Surrogate key
- Data Warehousing
After attending this session, you will be able to do point-in-time analysis in Power BI together with Microsoft Fabric and gain a whole new level of insight into how your data change over time and see the data as it existed at any given point in time.
In this session, we will explore various methods for tracking data history, so that you can provide your users with the ability to answer questions about how your data has changed over time. We will start by looking at some of the methods that can be used to track data history, such as snapshot tables and slowly changing dimensions. Then, we will explore how to implement these methods in Microsoft Fabric.
Topics:
- Point-in-time analysis
- Mutable vs. immutable data and stragies
- Incremental (Delta) loads
- Change data tracking
- Slowly Changing Dimensions
- Surrogate key
- Data Warehousing
After attending this session, you will be able to do point-in-time analysis in Power BI together with Microsoft Fabric and gain a whole new level of insight into how your data change over time and see the data as it existed at any given point in time.