Do your Power BI models suffer from “ambiguous relationships”? Have you expanded your vocabulary while encountering errors trying to relate multiple tables in a data model?
Data modeling is an essential skill in Power BI design and hard problems require creative solutions. In a recent webinar Lead Consultant Paul Turley identifies common challenges and demonstrates modeling techniques to resolve them.
Over the past five or so years, we’ve seen a surge in self-service BI. This means that the business intelligence tools are no longer only in the hands of IT, developers, and analysts, but also in the hands of business users. Sure, importing data and throwing it into a chart is easy to do in many of these tools including Power BI, Excel, and Power Query, but is this type of reporting enough?
For the casual business user these tools promote the idea of importing data, mashing it together into a single flat table like in Excel and maybe bring this into a spreadsheet where we can filter, group and aggregate columns; this is referred to this as flat spreadsheet based reporting.
This reporting has its place but when dealing with a large volume of data and more complex data structures, this will not meet all your business needs. This is where the dimensional model comes in and this is the first key to understand in your data modeling journey. Dimensional modeling is the go-to modeling approach 95% of the time for business intelligence data.
This demo heavy webinar will teach you all you need to know about building a data model with examples. Paul will discuss:
- Dimensional modeling rules; the process and steps
- The importance of role-playing dimensions
- Bi-directional filters
- Many to many relationships
- Disconnected tables and dynamic measures
- Plus, links to some important resources and guidelines
So, if you want to learn about data modeling in Power BI, this webinar is for you. Watch the complete presentation below.
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