User Profile
codyraptor
Resolver I
Joined 9 years ago
User Widgets
Contributions
Re: Data Modeling large Fact table with multi granularity vs Multi Facts
selimovd Checking in to see if you had a chance to look over this. The able above is just a simple example...but all 3 levels share dimensions such as State, Product, etc... I currently have the model has a star schema with 3 fact tables. However....The requirements continue to grow and the model is slowing. Just making sure I'm using best practice.Offset not showing value no rows
Here is my requirement: I need to show the Gross of child 2 on the row of child 1. See visual below.... Parent ID Child ID Child Date Type Gross Offset Gross Offset Gross 1 1 1/1/2023 norm $100 $250 1 2 1/5/2023 xfer $250 $100 I've created an offset calculation against a summarized table and it seems to work. I can see the value in the 'total', but the value will not show on the rows. I assume because they're being hidden. This is a STAR schema and Parent/Child/Date/Type are all different DIM tables. Gross is calculated in the FACT table. Any help is greatly appreciated. This is my current measure: CALCULATE( [gross], OFFSET( -1,SUMMARIZE( Fact, Fact[Parent ID], Fact[Child ID], Fact[Date]) , orderby([Parent ID] ,ASC,[Date],ASC) ,,PARTITIONBY([Parent ID]) )Re: Composite/Live connect slower than Import..same measure
lbendlin In this measure....I'm just doing a distinct count against the fact table and filtering 2 DIM tables. 100% of my joins between the DIM and Fact tables are 1 to many. Both DIM tables are ~7 rows...fact table is about 10M. I'm also using a true calendar table for any date references. It runs super fast and efficient in the main model...but just loses efficiency in the live connection for some reason. Can you explain 'query text - just the text'? Are you referencing the Dax code? If so...it's just Calculate(DistinctCount(fact_ID),not fact_type in {'X','XA'})Composite/Live connect slower than Import..same measure
I have an import model published to the PBI cloud. I'm connecting another local model to it via DQ/Live connect and I've noticed a large change in performance. In the screenshot below...you can see the same exact measure being pulled in DAX studio for comparison. The screen on the right is the local import model. The left is the same measure. Is this expected or am I missing a way to optimize? I also noticed the FE and SE flipped as far as which was doing all of the work.Add local data to Live connection..causing 1Million row error
I have a single file that I'm adding to a remote DQ model via live connection. The only common join I have is the most granular being the ID. I don't have other common dimensions in my file. When I calculate anything...it causes the 1Mil row error because, I assume, PBI is pushing the calculation back to the cloud and calculating over every ID. Question: Is there a way to do a lookup function to add the dimensions needed to my file...so I can speed up the calculations and not rely on joining at the ID level? If not...what are my other options. It seems I need to create a temp table possibly...somehow joining at a higher level than ID. Much appreciate any help!Sort matrix by measure..but 2nd level rows ignore sort
Hey everyone. I have a simple matrix that sorts by volume. I also have a time calculation group for Current and PY and the ordinal is set to the correct sort order. However...sorting the Matrix overrides the sort order of the calculation group. Is there a way to sort the matrix by the volume measure...but ignore the sort for the calculation group?
