Course NT-PowerBID-BM Data modeling in Power BI Desktop
- A properly built data model is the foundation of analytics, so the topic of data modeling is one of the most important. In most Power BI trainings, data modeling issues are considered superficially, since this topic is too voluminous and requires a separate study. This training is completely devoted to data modeling.
- The training is practical - all the concepts and methods of the training participants will immediately be embodied in the data model. Thus, after training, in addition to knowledge, skills and abilities, students will have all practical cases with solved problems.
- The training raises the overall level of “data culture”.
Training duration:
- 8 academic hours
After completing this course, students will be able to:
- They will understand that data modeling is a separate activity of an analyst and carry it out as a separate stage of data analysis.
- They will be able to create links between tables of the model and manage them, using numerous nuances and subtleties of link settings.
- Will be able to create in Power BI Desktop data models of the "star" and "snowflake" types.
- Will be able to use Power functionality for modeling Query and DAX expressions
Audience Profile
- Analysts who create Power BI Desktop reports
- Analysts who design data models in Excel using Power Pivot
- Database developers
- Excel users whose work is in one way or another related to data analysis
- Experts familiar with data modeling (will be able to structure existing knowledge)
Before attending this course, students must have:
- knowledge of Power BI Desktop, Power Query and DAX at a basic level.
- The concept of data modeling.
- Conceptual, logical, physical modeling.
- Modeling Toolkit in Power BI Desktop.
- Power data model BI Desktop, the stages of its construction.
- Connections, their purpose and creation.
- Relationship types (one-to-one, one-to-many, many-to-many).
- Features of links, work with links of each type.
- Normalization and denormalization of tables.
- Explicit and implicit measures.
- Star and snowflake data models.
- Tables of dates and measurements.
- Key fields.
- Surrogate keys.
- Role measurements.
- Degenerate measurements.
- Fact tables with and without metrics.
- Active and inactive links.
- Direction of cross-filtering (one- and two-way cross-filtering).
- Managing Relationships with DAX
- Create junction (auxiliary) tables with Power Query and DAX.
- Date tables. Their use as connecting.
- Various types of table joins (join kind). Working with inconsistent data.
- Working with unrelated tables.
Sign up for the closest date
Copyright © 2024 Networking Technologies