I'm trying to build a Pivot table out of 4 tables that i have loaded in PowerPivot.
the information in the rows of the Pivot is like this:
Region
account
Products
One of the tables has the forecasted values for all 4 quarters for each Region but when i add it as Sum Values it repeats the entire number for each product but i just want the total. Is there a way to fix it without having to change the color of the font to white to hide it?
Without more info can't be sure, but this looks like you have not set up the model to support the Quarterly Forecast Measures in PowerPivot. To get this to work, there needs to be one-to-many relationships between identifying fields in each table.
PowerDax answered based on the assumption that you intended for the Quarterly Forecast to roll up to the region because you phrased you're question to indicate the forecast data is at the regional granularity.
If the forecast data is in one fact table, and the EXT_SELL_PRICE is in another, you will need to set up dimension tables each containing unique lists of the members of each field you are using to slice and dice the report (looks like End User Region, Child Customer, forecast product name). Relate all you're fact tables (tables that contain you're actual data) to these and put the dimension table fields in the Rows area of the pivot table. Then the measures will have some way of understanding how they relate to the rows they are being applied to.
Hope that helps
it would be best for these to be actual calculated fields rather than implicit calculated fields (i.e. dropping the column onto the pivot table). This way you can utilize the isfiltered function to drive what you are looking for.
i.e. if your data is at this granularity:
Region Customer Product Ext_Sell_Price Q1 Q2 Q3
Brazil Acuntia 39XX 17246 743799 672599 748339
Brazil Acuntia 51XX 130918 743799 672599 748339
or you have the sales table and a region forecast table with a relationship to the sales table, you could check to ensure customer/product were not filtered in order to show the forecast:
Q1 Total:=IF( ISFILTERED( Table1[Customer]) || ISFILTERED( Table1[Product]), BLANK(), MIN( Table1[Q1]) )
Related
I have a table with more than 1 million rows of data so I can't put the information into Excel. The first column is the identifier and the second column is the percent increase on that identifier. The table records all the increases over a year so the ID entries in the first column can have more than one increase during the year.
I want to calculate the total increase. If the data was small enough to fit in excel I would just pivot the table and make the rows the ID in the Rows bucket and the Product of the Increase in the Values bucket. This give me one row for each unique ID and the total percentage increase for the year.
The matrix visualization in Power BI doesn't help since it doesn't have a similar Product summarization. That and there are more than 1 million unique IDs in the dataset so I can't export it due to the 150K row limit. I need to create a new table in BI that does the same thing because I want to bring in related data from another table that includes categories and then average the category.
Is there a way to do this? Please let me know any questions you have and if you need any additional information or clarification. Thanks.
Here, I have some vehicle data, attached with some corresponding information about the where the owners of these types of vehicles live, and their average house price.
Clearly the house price/location doesn't directly affect the vehicle value, but is useful for statistical inference.
What I want to do is to create a pivot table - however when considering the average vehicle value, the pivottable sums up each type of Vehicle/Model class multiple times as shown below:
And so, while the average House Price column in the pivottable is correct, the vehicle value is incorrectly counted multiple times (with respect to the Vehicle Make).
No, there is no DistinctSum function in the pivot table. The only thing that comes to mind is to add an additional column in the base table where the required values can be calculated. For example, in the column 'Distinct value' you can insert the following formula:
=D2/SUMPRODUCT((A2=$A$2:$A$13)*(B2=$B$2:$B$13))
it calculates the Value / Count of values for each car and model and then in the pivot table sum this column.
I am having issues translating the following formula to a pivot table; either through a regular pivot table, or through DAX and powerpivot.
=SUMPRODUCT((C$2:C$11)*(D$2:D$11)*(A$2:A$11=A2)*(B$2:B$11=B2))/SUMIFS(D$2:D$11,A$2:A$11,A2,B$2:B$11,B2)
The background is, I have a number of products that appear on an e-commerce site, and I need to find out their price per day. However, these prices change daily, based on things like promo codes, visitor location etc. Therefore, I need their weighted price based on the number of visitors that saw a particular price.
Can anyone help with this translation, or alternatively, offer a better way to approach this problem?
PS- I need it in a pivot table due to the volume of data. At 250,000 rows, standard Excel cannot handle this formula.
The following is in Excel 2010 sans Powerpivot. However, the general approach should work:
Explanation:
I added a column that multiplies the Prices and Visits. The pivot table uses Dates, then Product SKU as the row labels. Then I added a calculated field that divides the Price*Visits by the Visits.
I think I've got a relatively easy problem here on my hands, just having trouble getting it to work. Let me preface this by saying I'm new to DAX.
Consider the following PowerPivot Data Model :
It consists of a Sales Records table, which is joined to a Date lookup table, as well as a "Daily Expenses" table. The "Daily Expenses" table stores a single value which represents the averaged cost of running a specific trading location per day.
It's extremely easy to produce a PivotTable that provides me with the total Sales Amount per store per [insert date period]. What I'm after is a DAX formulation that will calculate the profit per store per day - ie. Total Sales minus DailyExpenses (operating cost):
In theory, this should be pretty easy, but I'm confused about how to utilise DAX row context.
Failed attempts:
Profit:=CALCULATE(SUM(SalesInformation[SaleAmount] - DailyStoreExpenses[DailyExpense]))
Profit:=CALCULATE(SUM(SalesInformation[SaleAmount] - DailyStoreExpenses[DailyExpense]), DailyStoreExpenses[StoreLocation])
Profit:=SUM(SalesInformation[SaleAmount] - RELATED(DailyStoreExpenses[DailyExpense])
etc
Any help appreciated.
Zam, unfortunately your failed attempts are not close :-)
The answer, and best practice, is use a 4th table called 'Stores' which contains a unique record per store - not only is this useful for bringing together data from your two fact tables but it can contain additional info about the stores which you can use for alternative aggregations e.g. Format, Location etc.
You should create a relationship between each of the Sales and Expenses tables and the Store table and then use measures like:
[Sales] = SUM(SalesInformation[SaleAmount])
[Expenses] = SUM(DailyStoreExpenses[DailyExpense])
[Profit] = [Sales] - [Expenses]
Provided you have the Date and Store tables correctly linked to the two 'Fact' tables (ie Sales and Expenses) then the whole thing should line up nicely.
Edit:
If you want to roll this up into weeks, years etc. and you have no kind of relationship between expenses and the calendar then you'll need to adjust your expenses measure accordingly:
[Expenses] = SUM(DailyStoreExpenses[DailyExpense]) * COUNTROWS(DateTable)
This will basically take the number of days in that particular filter context and multiply the expenses by it.
I am trying to make a pivot table that has a list of inventory on one axis and customers on another axis. With this table I could replace all non-'1' values in the table with 1s and then use the column count to determine the total number of items purchased by each customer. However, Excel claims that there's far too much information and that it wouldn't be able to complete the task. Is there another way to do this that doesn't involve pivot tables?