I'm working on a SSAS cube to allow user to analyze some sales.
So, I created a fact table to record all sales and few dimensions to browse inside data (category / location & store, etc...).
This is a example of the fact table output (from SQL Server Management Studio) :
When I browse my cube, I can review all sales including date, quantity, etc.
However, when I add some fields like the "unit price" or the "unit cost", it returns me a strange result probably due to an aggregate behavior.
It seems it return the sum of all matching rows (aggregateFunction property).
How to simply display the unit price of a sale without apply any calculation to the unit price column. The None value for the AttributeFunction display BLANK/NULL.
If your unitCost and unitPrice are the same for each product (I mean unitCost can be only 77.6 for product_id = 2), you can just use average (or even emulate average by SUM/COUNT) - but only for product dimension on axis!
Another dimensions will show real average values.
Maybe it's better to use this 'static' fields like attribute properties in 'Product' dimension? But you still need to add some logic to choose one value for several (or all) product members selected.
Related
I'm trying to subtract a value in one field from a value in another table, depending on ID number using Filemaker Pro 19.x. I thought I'd done this before without any problems but now it isn't working and I don't know why.
First, I want to do this in a calculation field, not in a script. I don't understand scripting at all and use it only when there is no alternative. In this case, I think a calculation field should work.
I have 2 tables, I'll call them "Data" and "Categories"
Both tables have the field "CID" "Category ID".
The CID fields in both tables are linked in the Relationship Editor
The Data table has a field "Product ID"
The Categories table has several fields related to products. Two of those are "MIN PID" and "MAX PID". These are the minimum and maximum product ID numbers.
Product IDs are assigned in ranges. If it is within a certain range, it has to belong to a certain category. These categories have CID numbers.
To assign the CID number to the products listed on the Data table, I did run a script that essentially recreated all the data within the Categories table. It was inefficient (in my eyes) because the data was sitting right there in the table. I couldn't figure out how to reference it, so I gave up and ran the script instead. The other problem is that if the CID ever changes for a product, I have to rerun the script (or someone else, who might not know about the script)
That said, I now have the correct CID assigned for all 62 product categories. What I want to do now is to use the CID MIN and CID MAX values (among others) in calculation fields in the Data table.
For instance, if the product ID is "45,001", it belongs to the Category "16", which has a MIN value of "30,000" and a MAX value of "50,000". I want to subtract the "30,000" from the "45,001", (PID - CID MIN) to return the result "15,001". This allows me to locate a product within the category. Instead of being "Product 45,001", it will be "Product 16.15001".
The calculation I tried is:
If (CID = CID::CID ; PID - CID::CID MIN)
The result is a huge group of records where this field is empty.
I also tried:
PID - CID::CID MIN
Again, no results.
Both tables have the field "CID"
The two CID fields are linked in the relationship editor.
I have tried this with a test file and it works perfectly. It does not work in the database I am working within.
What am I doing wrong?
I have imported my GA4 data into Google Data Studio and am trying to see how many giftcards have been sold by their value.
The item revenue metric in GA4 is equal to the giftcard value (i.e. revenue = $200 therefore $200 giftcard was sold).
I want to breakdown sales by giftcard value like so:
Giftcard (revenue)
Count
$200
4
$250
3
$300
6
To do this, I need to set a copy of item revenue as a dimension rather than a metric.
In Google Data Studio, I can create a calculated field with the following formula that should convert the item revenue into text:
CAST(Item Revenue AS TEXT)
The problem I'm having is that while the formula sets the field type as text, it is still regarded by GDS as a metric and can't be used as a dimension.
Even when I try to add text, GDS still recognises the field as a number:
CONCAT(CAST(Item Revenue AS TEXT), " giftcard")
To use a metric as a dimension you can make a combination of data. When defining the graphic element (table, for example) and the respective data source, just create a data combination, but do not combine the data with any other source and just define the combination with the initial data itself. So you will have the same data structure only through a combined structure.
When making a combination of data, data studio recognizes all calculated fields (metrics) as dimensions. Thus, it is possible to make the conversion.
I have a table that shows the recurrence of purchasing a product, with the columns: product_id, report_date, quantity.
I need to list in a table the products that are more than 50 days unsold. The opposite I managed to do (list those that were sold in the last 50 days) but the opposite logic has not yet been able to implement.
Does anyone have any tips?
An example of the table:
product_id,date,report_date,quantity
329,2019-01-02 08:19:17,2019-01-02 14:34:12,6
243,2019-01-03 09:19:17,2019-01-03 15:34:12,6
238,2019-02-02 08:19:17,2019-03-02 14:34:12,84
170,2019-04-02 08:19:17,2019-04-02 14:34:12,84
238,2019-04-02 08:19:17,2019-04-02 14:34:12,8
238,2019-04-02 08:19:17,2019-04-02 14:34:12,100
238,2019-08-02 08:19:17,2019-08-02 14:34:12,100
238,2019-10-02 08:19:17,2019-10-02 14:34:12,100
170,2020-01-02 08:19:17,2020-01-02 14:34:12,84
170,2020-01-02 08:19:17,2020-01-02 14:34:12,84
There are many steps to do this task. I assume the date column is the one to work with. Your example from table includes duplicated entries. Is it right that at the same time the order is there twice?
So here are the steps:
At first add an calculated field date_past to your dataset:
DATE_DIFF(CURRENT_DATE(),date)
To the dataset add a filter SO_demo with:
include date_past<30
Then blend the data with it self. Use product_id as Join key. Only the 2nd dataset has the SO_demo filter. Add to the dimension of this dataset the calculated field sold_last_30_days with the formula "yes".
In the table/chart to display add a filter on the field include sold_last_30_days is Null.
I'm using ssas tabular (powerpivot) and need to design a data-model and write some DAX.
I have 4 tables in my relational database-model:
Orders(order_id, order_name, order_type)
Spots (spot_id,order_id, spot_name, spot_time, spot_price)
SpotDiscount (spot_id, discount_id, discount_value)
Discounts (discount_id, discount_name)
One order can include multiple spots but one spot (spot_id 1) can only belong to one order.
One spot can include different discounts and every discount have one discount_value.
Ex:
Order_1 has spot_1 (spot_price 10), spot_2 (spot_price 20)
Spot_1 has discount_name_1(discount_value 10) and discount_name_2 (discount_value 20)
Spot_2 has discount_name_1(discount_value 15) and discount_name_3 (discount_value 30)
I need to write two measures: price(sum) and discount_value(average)
How do I correctly design a star schema with fact table (or maybe two fact tables) so that I in my powerpivot cube can get:
If i choose discount_name_1 I should get
order_1 with spot_1 and spot_2 and price on order_1 level will have value 50 and discount_value = 12,5
If I choose discount_name_3 I should get
order_1 with only spot_2 and price on order level = 20 and discount_value = 30
Fact(OrderKey, SpotKey, DiscountKey, DateKey, TimeKey Spot_Price, Discount_Value,...)
DimOrder, DimSpot, DimDiscount, etc....
TotalPrice:=
SUMX(
SUMMARIZE(
Fact
,Fact[OrderKey]
,Fact[SpotKey]
,Fact[Spot_Price]
)
,Fact[Spot_Price]
)
AverageDiscount:=
AVERAGE(Fact[Discount_Value])
Fact table is denormalized and you end up with the simplest star schema you can have.
First measure deserves some explanation. [Spot_Price] is duplicated for any spot with multiple discounts, and we would get wrong results with a simple SUM(). SUMMARIZE() does a group by on all the columns passed to it, following relationships (if necessary, we're looking at a single table here so nothing to follow).
SUMX() iterates over this table and accumulates the value of the expression in its second argument. The SUMMARIZE() has removed our duplicate [Spot_Price]s so we accumulate the unique ones (per unique combination of [OrderKey] and [SpotKey]) in a sum.
You say
One order can include multiple spots but one spot (spot_id 1) can only
belong to one order.
That's is not supported in the table definitions you give just above that statement. In the table definitions, one order has only one spot but (unless you've added a unique index to Orders on spot_id) each Spot can have multiple orders. Each Spot can also have multiple discounts.
If you want to have the relationship described in your words, the table definitions should be:
Orders(order_id, order_name, order_type)
OrderSpot(order_id, spot_id) -- with a Unique index on spot_id)
Spots (spot_id, spot_name, spot_time, price)
or:
Orders(order_id, order_name, order_type)
Spots (spot_id, spot_name, spot_time, order_id, price)
You can create the ssas cube with Order as the fact table, with one dimention in the Spot Table. If you then add the SpotDiscount and Discount tables with their relations (SpotDiscount to Spot, Discount to SpotDiscount) you have a 1 dimentional.
EDIT as per comments
Well, the Fact table would have order_id, order_name, order_type
The Dimension would be made up of the other 3 tables and have the columns you're interested in: probably spot_name, spot_time, spot_price, discount_name, discount_value.
I have combined two datas which are price 2013 and volume 2013 to create one pivot table. But how can I find revenue (Volume multiply price) by using pivot table? Please help. Thanks. My column field there included Price from data 1 and volume from data 2.
Switch one of the fields to Σ Values (Volume would seem to be the more sensible) and add a Calculated Field (PivotTable Tools, Options > Tools - Formulas) say Named: Revenue and with Formula: Volume*Price.
However depending upon your version of Excel and your data, you may receive incorrect results (eg in the GT row for revenue).