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Hello. I need help with the calculation, I want to optimize it, but don't know how. I'll try to explain:
I have two survey questions. Fist question assignes 8 brands per person. So I have it stored in the database like 8 rows per person, I have person ID, brand order(1-8) and the brand assigned to each order per person.
In next question those 8 brands are asked in the matrix question, where the rows headers are 10 attributes. So person selects 1+ brand associated with each attribute. So in the database, for each person for each attribute, only selected brands stored.
One remark about attributes, I then group them into 2 factors, so I have 5 attributes per factor.
Then I have two tables:
Person ID | Brand Order | Brand | Country |
1 | 1 | UK | |
1 | 2 | Microsoft | UK |
1 | 3 | Amazon | UK |
1 | 4 | Meta | UK |
1 | 5 | Telegram | UK |
1 | 6 | Samsung | UK |
1 | 7 | IMB | UK |
1 | 8 | Dell | UK |
2 | 2 | Oracle | USA |
Person_id | Country | Brands | Attributes | Factors |
1 | UK | Have integrity | Factor 1 | |
1 | UK | Dell | Stands for something I believe in | Factor 1 |
1 | UK | Oracle | Are reliable | Factor 1 |
1 | UK | Dell | Is a visionary | Factor 1 |
2 | USA | Oracle | Plays an important role in society | Factor 1 |
2 | USA | Dell | Will have a clear role in the future | Factor 1 |
3 | Germany | IMB | Will be popular in the future | Factor 2 |
3 | Germany | Samsung | Cares about its environmental impact | Factor 2 |
3 | Germany | Are innovative | Factor 2 |
I calculate the association metric, per each brand per each country, I calculate the number of times it was selected per attribute and divide by the number of times it was exposed in total(in other words, number of people selected it/number of people was asked about it)
The formula:
Because I will also apply filters, like age group, gender, etc.
Thanks in advance, really need help, have been struglling with it for a long time already
It seems like your Power BI model is experiencing performance issues due to the complexity of the calculations and the size of the dataset. Here are some suggestions to optimize your model:
Use Relationships in the Data Model:
Use RELATED() Function:
Filter Context Optimization:
Consider Aggregating Data in Query Editor:
Use Measures Wisely:
Data Model Size:
Indexing and Sorting:
Partitioning:
Optimize Visuals:
DAX Studio:
Remember to test each optimization step to ensure it improves performance. Additionally, some trade-offs may be needed between performance and the level of detail displayed in your reports.
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