Ok, I have watched many videos and read all sorts and I think I am nearly there, but must be missing something. In the data model I am trying to add the ytd calc to my product_table. I don't have unique dates in the product_table in column a and also they are weekly dates. I have all data for 2018 for each week of this year in set rows of 20, incrementing by one week every 20 rows. E.g. rows 1-20 are 01/01/2018, rows 21-40 are 07/01/2018, and so on.
Whilst I say they are in set rows of 20, this is an example. Some weeks there are more or less than 20 so I can't use the row count function-
Between columns c and h I have a bunch of other categories such as customer age, country etc. so there isn't a unique identifier. Do I need one for this to work? Column i is the sales column with the numbers. What I would like is a new column which gives me a ytd number for each row of data which all has unique criteria between a and h. Week 1 ytd is not going to be any different. For the next 20 rows I want it to add week1 sales to week2 sales, effectively giving me the ytd.
I could sumproduct this easily in the data set but I don't want do that. I want to use dax to save space etc..
I have a date_table which does have unique dates in the main_date column. All my date columns are formatted as date in the data model.
I have tried:
=calculate(products[sales],datesytd(date_table[main_date]))
This simply replicates the numbers in the sales column, not giving me an ytd as required. I also tried
=calculate(sum(products[sales]) ,datesytd(date_table[main_date]))
I don't know if what I am trying to do is possible. All the youtube clips don't seem to have the same issues I am having but I think they have unique dates in their data sets.
Id love to upload the data but its work stuff on a work computer so cant really. Hope I've painted the picture quite clearly.
Resolved, after googling sumif dax, mike honey had a response that i have adapted to get what i need. I needed to add the filter and earlier functions to my equarion and it ended up like this
Calculate (sum(products[sales]),
filter (sales, sales[we_date] <=earlier(sales[we_date]),
filter (sales, sales[year] =earlier(sales[year]),
filter (sales, sales[customer] =earlier(sales[customer]))
There are three other filter sections i had to add, but this now gives me the ytd i needed.
Hope this helps anyone else
Related
I have a table in Access that is setup like the one in the photo. What I need to do is this:
For each part no, I want to sum the total Qty for each month and type (Ordered and Demand). Then I need to cap the qty in the rows where the type is = to Orders to the value of the Qty where the type is = to Orders, when the sum of the Qty for Ordered is greater than Demand. Let me try to explain it another way.
I want to look at a subset of the master data, in this case the subset is by part no (rows with identical part numbers). For this subset I want to have two sets of sums. 1. The sum of qty with type = Ordered AND 2. a sum of qty with type = Demand. If the sum for Ordered is greater than demand, I want to change the Qty for Ordered to be the value of the Qty for Demand.
Essentially, the business reason is that for reporting purposes the total Qty for Ordered shouldn't be more than Demand in a given month, for a part number.
Looking at the photo, the rows in red will need to change because the sum of the qty is 30, which is greater than the sum of qty for the green rows (25). The red rows qty should be changed to 20 and 5 to match the green rows.
Whew, hope this made sense because it is hard to explain. I have tried many things for a couple weeks now, and I am a bit fuzzy on the details so I will just give a high level. Ok so what have I tried:
I have tried to join the table to iself, using part no (and date I believe) to join on, but that doesn't work because the sum would somehow be incorrect sometimes.
Pivot the table, using the transform and pivot functions in Access but it's important for me to keep the individual dates in tact and when I pivoted it I had to roll it up on a month basis. This gives me the row structure I need to make the changes but I don't know how to get back the original date format after I am done.
I am guessing I need some VBA code that loops through each part no, but I am not big on VBA code and I don't have much time to learn it. Any suggestions? I know this is long winded but its a complicated problem (at least for me). Thanks in advance.
I have a Fact table that holds what are more or less, sales goals. The ETL process that populates it, generates 12 "weighted" values into seperate rows, one per month. Each row however, also includes a field that holds the yearly value. I do this with unpivot. This all works. Now Im trying to get at this data in the cube with an SSRS report. The problem seems to be that I can query and see the results that include either the yearly goal values or the monthly, weighted values, but not both in the same set.
[update for fact table details]
My Fact table looks something like this:
FK_Account
FK_User
Target
Projected
GoalYear
FK_DateKey
FK_Dept
MonthlyWeightedTarget
MonthlyWeightedProjected
When I load this fact table via the ETL, I get the date key associated with each monthly value (MonthlyWeightedTarget). That will be 12 seperate records, but each one will have the same yearly value. Im not including next years value as a seperate column, because there are seperate records already associated with that year.
Basically, the users define a set of goals associated with a given year. Then I am applying a "weighting" to generate 12 seperate "monthly" records, which total up to the yearly target goal. Hope this makes sense.
What I need to see is something like this result:
Account Name
YTDgoal
YearGoal
NextYrGoal
I created a calculated member for the NextYrGoal, but now Im not sure I even need it.
What would be a good approach for handling the above (getting the ytd, yearly and next year values) ?
If I was getting at these values with TSQL, I would sum on the monthly values, and just include the associated yearly and next years values, grouping by account, year-goal, next-year-goal
I'm currently working on a project in which I want to aggregate data (resolution = 15 minutes) to weekly values.
I have 4 weeks and the view should include a value for each week AND every station.
My dataset includes more than 50 station.
What I have is this:
select name, avg(parameter1), avg(parameter2)
from data
where week in ('29','30','31','32')
group by name
order by name
But it only displays the avg value of all weeks. What I need is avg values for each week and each station.
Thanks for your help!
The problem is that when you do a 'GROUP BY' on just name you then flatten the weeks and you can only perform aggregate functions on them.
Your best option is to do a GROUP BY on both name and week so something like:
select name, week, avg(parameter1), avg(parameter2)
from data
where week in ('29','30','31','32')
group by name, week
order by name
PS - It' not entirely clear whether you're suggesting that you need one set of results for stations and one for weeks, or whether you need a set of results for every week at every station (which this answer provides the solution for). If you require the former then separate queries are the way to go.
I've searched here and elsewhere on the web and have not found this exact problem/solution.
I'm building an rdlc report using the MS reportViewer - the report I'm creating is based on an existing spreadsheet where the average price across 6 months is calculated individually for each month, then the average of those prices is calculated as the 6 month period average price. Whether I agree with that methodology or if it's correct is irrelevant, I just need to know how to get an rdlc to do this.
For example:
Month Price1 Price2 Delta
May-12 $31.54 $30.03 $1.51
Jun-12 $36.27 $34.60 $1.67
Jul-12 $44.19 $42.00 $2.19
Aug-12 $38.96 $37.06 $1.90
Sep-12 $36.89 $35.08 $1.81
Oct-12 $35.57 $33.97 $1.60
Average $37.24 $35.46 $1.78
(sorry for the lack of a screen snip, I'm new and the system won't let me post an image...)
I've created a tablix that does the monthly averages computation - I use a group in the table to group the 6 months of data by month (and then hide the hourly price data so you only see the month total row) but I'm stuck on how to calculate the bottom row of the table which is the average of each column. (the average of the averages is not the same as the average of all 6 months of prices from the underlying data - that's what I've learned in this process... IOW, that was my first solution :-) )
What I tried to do to get the average of the averages was give the month total cell a name, MonthlyAvgPrice1, then in the bottom row, used this expression:
Avg(reportitems!MonthlyAvgPrice1.Value)
As I kind of expected, this didn't work, when I try to run the report, it gets a build error saying "The Value expression for the textrun 'Price1PeriodAvg.Paragraphs[0].TextRuns[0]' uses an aggregate function on a report item. Aggregate functions can be used only on report items contained in page headers and footers."
Hopfully I've explained this well, does anyone know how to do this?
Thanks!
-JayG
Actually it is not clear from the question that how are you in particular binding the data to the report items, But from the given information what I understand is that you can
Try like this:
Right Click the tablix row and insert a row below
In the cell where you want to have this Average of Averages insert the following expression
=Sum(Fields!Price1.Value)/6
and similarly insert expression =Sum(Fields!Price2.Value)/6 and =Sum(Fields!Delta.Value)/6 in the other cells where you want to display the Averages
Of Course, you will change the Field names Price1,Price2 etc to the fields that you are getting the values from.
HTH
Suppose ,I have a table which has all the billing records. Now I want to see the sales trend for a user given time duration group by each 3 days ...what should be the sql query regarding this?
please help,Otherwise I am gone ...
I can only give a vague suggestion as per the question, however you may want to have a derived column with a standardised date (as per MS date format, just a number per day) that you could then use a modulus (3) on so that days are equal per 3 day period. You can then group and aggregate over this column to get the values for a 3 day period. Obviously to display the date nicely you would have to multiply back and convert your column as well.
Again I'm not sure of the specifics, but I think this general idea could be achieved to get a result (may well not be the best way so it would help to add more to the question...)