Let's improve the Tabular Model by Combining queries
2022TL; DR
Cleaning and reshaping data with Power Query is one of the best parts of designing and delivering analytical reports with Power BI. This session will demo several scenarios in which combining queries could be the perfect solution for the optimal tabular model.
Session Details
Cleaning and reshaping data with Power Query is one of the best parts of designing and delivering analytical reports with Power BI. This "full of demo" session will demonstrate several scenarios in which Combining queries could be the perfect solution for the optimal tabular model.
Some examples about what will be covered using Combining queries in this How's style session are the following:
Identify entities and attributes.
Respect the star model design
Protect the fact tables model
Data quality tasks
Version control of data
Management of excluded sets
VLookUp vs. Aggregates and
Role-Playing Dimensions
3 things you'll get out of this session
Speakers
Ana Maria Bisbe York's other proposed sessions for 2026
Querying data and metadata with T-SQL, M and DAX - 2026
SQL Fabric, the perfect combination of experience and youth - 2026
To filter or not to filter, that is a question - 2026
Ana Maria Bisbe York's previous sessions
Let's define Entities and attributes for tabular models in 20 minutes.
Examples from real-life projects that demonstrate the issue and improve the design of entities for the tabular models.
Lets play with a date field & Time Intelligence in Power BI
Date fields play an important role in virtually all cases of advanced analytics. The "problem & solution" style session can be very useful given the large number and variety of scenarios that may arise
Lets do the cleansing with M and / or Python languages
This short session will cover some scenarios of cleansing data in Power Query using M, Python, or both languages.
Some transformations that can save your ETL in Power BI
To build analytical models, we need to start by extracting, transforming, cleaning, preparing and loading the data. This session analyzes a set of scenarios that may happen during the ETL step using the Power Query in Power BI.