Describe Power BI Desktop models Flashcards
What is the primary focus when developing reports and dashboards in Microsoft Power BI?
Understanding the questions that users will ask and designing the semantic model to support visualizations.
What tasks are involved in developing a semantic model in Power BI Desktop?
Connecting to data, transforming and preparing data, adding DAX calculations, and publishing the model to Power BI.
Why is it important to design an optimal semantic model?
To ensure good query performance, minimize data refresh times, and reduce the use of service resources such as memory and CPU.
What is the advantage of using fewer resources in Power BI?
More models can be hosted at a lower cost.
What is the role of Data Analysis Expressions (DAX) in Power BI?
DAX is used to define business logic and calculations within the semantic model.
What is a star schema in the context of Power BI semantic models?
A design approach commonly used by relational data warehouse designers that presents a user-friendly structure and supports high-performance analytic queries.
What are the two types of tables in a star schema?
Fact tables and dimension tables.
What is the primary role of a fact table?
To store an accumulation of rows representing observations or events, such as sales orders or stock movements.
What do dimension tables describe?
Business entities such as people, places, products, or concepts.
What is a key column in a dimension table?
A unique column that doesn’t contain duplicate values and should never have missing values, used to relate to fact tables.
How are dimension tables related to fact tables in a star schema?
Using one-to-many relationships, allowing filters and groups applied to dimension table columns to propagate to the fact table.
Why is it not recommended to relate a fact table directly to another fact table?
It goes against the principles of star schema design, which emphasizes clear relationships between dimension tables and fact tables.
What is an analytic query in Power BI?
A query that produces a result from a semantic model, typically written as a Data Analysis Expressions (DAX) query statement.
What are the three phases of an analytic query in Power BI?
Filter, Group, and Summarize.
What does the filtering phase in an analytic query do?
Targets data of relevance by applying filters to the report, a specific page, or a specific visual.
What is the purpose of the grouping phase in an analytic query?
To divide query results into groups.
How does the summarizing phase function in an analytic query?
It produces a single value result, often using methods like sum or count.
Can all report visuals in Power BI filter, group, and summarize data?
No, some visuals like slicers don’t summarize, and card visuals are not concerned with grouping.
What are the main elements involved in configuring a report visual in Power BI?
Visual type selection, mapping semantic model fields, configuring mapped fields, and applying format options.
What are the three types of model resources used to configure a visual in Power BI?
Columns, hierarchy levels, and measures.
What is the primary use of columns in configuring report visuals?
To filter, group, and summarize data.
Can hierarchy levels be used to summarize data in Power BI?
No, hierarchy levels can only be used to filter and group data.
How are measures typically used in report visuals?
Measures are used to summarize data and can filter data when applied as a visual-level filter.
What is a common summarization method for numeric columns in Power BI?
Sum, count, distinct count, minimum, maximum, average, median, standard deviation, or variance.
