!! This is a clickbait post to get your vote for some missing features in Power BI !!
Although this might not be what the inventors of Power BI had in mind, large lots of folks are trying to create classical financial statements in it. And putting aside the afford that might go into getting the numbers right, there is still a major drawback to swallow:
Today I want to share a scenario where a running total calculation in the query editor saved a model that run out of memory when done with DAX:
The model couldn’t be refreshed and returned out of memory error with a calculated column in the fact table of over 20 Mio rows (from a csv-file). A running total should be calculated for each “JourneyID”, of which there were over 1 Mio in the table itself. This rose memory consumption during refresh by over 300 % – until it finally errored out:
Besetzung =
CALCULATE (
SUM ( Fact[Entries] )
– SUM ( Fact[Exits] );
FILTER (
ALLEXCEPT ( Fact; Fact[JourneyID] );
Fact[StopId]
<= EARLIER ( Fact[StopId] )
)
)
This is a post about a feature request, that definitely would make my life easier (and I guess others’ too):
Evaluation context and its transition is one of the hardest concepts in DAX and I would find it extremely helpful, if syntax highlighting would assist us here. Let the colour of the table name show whether the expression will be evaluated:
Edit 14-Dec-2017: Now that we can right-align text measures in PowerBI, a SWITCH-measure like here: http://www.thebiccountant.com/2017/04/24/kpis-in-easy-profit-and-loss-for-powerbi/#comment-719 is the best alternative in my eyes. No need to read on 🙂
As shown in my last part of the Easy P&L-series, Power BI unfortunately still lacks some fundamental formatting options like:
So for the moment I choose between the following workaround-options:
For both options the preparations are the same:
Today I’ll show you a very useful technique how to deal with a JSON record that contains a wild mixture of different elements like this:
If you click on one of the expandable elements, their content will be shown, but you’ll loose all the “surrounding” information (metadata) that is visible now. This is often an issue, regardless if you want to create multiple tables from it to build a star-schema or just need a handful of fields or a denormalized table. But with a little help from M, you’re good to go:
Table.FromRecords( { MyJsonRecord } )Will returns this:
With this move, every expansion of one of the expandable elements will keep the existing data in place:
Simply expand one element after each other to create a denormalized table
For multiple tables, keep this query and reference it to create you (sub-)tables. Always keep the Id-column as the key (!) to combine all the tables in your data model later. (Provided you use this in a function for multiple entities/series)
Best is to play with it, so just past this code into the advanced editor:
If your JSON-record has a different structure with “just” header and data in different fields, this technique will be more suitable for you: http://www.thebiccountant.com/2016/04/23/universal-json-opener-for-quandl/
Enjoy & stay queryious 🙂
Following up on the BOM-explosion: A comment reminded me that I had missed to present the costing techniques to calculate the total costs of each (sub)-product.
What I had shown is how to “aggregate” from parent down to child-level to retrieve the total quantity of each component within a BOM (“How many of each (sub-) components do we have to order (or build) for that bike?”) (1).
Now we reverse the aggregation direction and aggregate the total (!) quantities back up to the parents (2).
And, as this doesn’t make too much sense in an economical way, the second aggregation will be their prices (3). This will give us the sum of all part-costs (“How much will the order of all the parts cost us?”). This is also very useful for planning purposes or reconciliation of prices for intermediate products with your master data.
And if your model holds sales-data as well, you can calculate the totals costs of your total sales within each period. (4)