Problem:I am trying to make a Inventory Management Database on Microsoft Access 2010, and since i needed records date wise my Table looks like follows
SKU 2016-03-16 2016-03-17 2016-03-18 ... Total
AAA 10 -5 15 ... 20
BBB 05 05 25 ... 35
CCC 06 -5 24 ... 25
This way i wanted to add records for each day, but i am unable to make a "Total" column which will total all the columns (Sum(Columns*))
I am aware of sum and groupby but that works across multiple rows i am looking for something which can do the same for column
Expected Solution: A way either by Sql Query or VBA to total all the columns for SKU AAA,BBB,CCC, if not possible to total in the same table then i am open to total the columns in a new table.
Such a table is normally result of pivoting summary data. Real data would look like:
SKU, Date, Quantity
...
Then probably you would want to create a PIVOT table using SKU for rows, Date for Columns and Quantity for data (default operation is SUM). It would have the row totals by default.
It may have been named crosstab, cross tab .. or so in Access 2010.
(you may want to do the pivoting in Excel)
Related
Trying to add a column that counts distinct customers in snowflake based on criteria that changes for every row i.e. needs to count customers between 52 weeks before current week_ending date to current week_ending date.
The query that goes like
select week_ending, sales, last_year_cust_count
from table where year = 2022
now i want the last_year_cust_count to have distinct customers between 52 weeks before week_ending till current week_ending and this needs to show following results as example
Week_ending
Sales
last_year_cust_count
02/01/22
$300
3479
09/01/22
$350
3400
16/01/22
$450
3500
... and so on
The optimal way to solve this over complex structure, is to use a bitmap, and then roll that up to the projections you over.
You should read Using Bitmaps to Compute Distinct Values for Hierarchical Aggregations
The simple, non-performant way is to self join and throw processing power at it.
select a.week_ending, a.sales, count(distinct b.customer) as last_year_cust_count
from table_a as a
join table_a as b
on <filter that I cannot bothered writing to select last 52 weeks base on years and weeks>
where year = 2022
I have a table with several time intervals as rows with one "total" row. I have four columns; car, bus, truck, and total, that refer to the number of vehicles leaving a warehouse at each time interval by category and the total number of vehicles at each time interval. My table looks like this:
time car truck bus total
12-6am 10 15 10 35
7am-12pm 8 12 8 28
Total 18 27 18 63
I want to create a percent total row that takes the total value in each row (35 and 28) and divides it by the maximum value in the total row (63).
How do I do this?
If you look at the schema of your table, it doesn't make sense to have an extra row in it, but only an extra column.
However, even that is a bad idea. A database is not a spreadsheet, where you have largely free-form data. It's a collection of tables. Total rows should be calculated with SELECT statements, not make some attempt to have them in the table. Unlike a spreadsheet, Postgres won't auto-update that as rows are added and deleted. (Note: Yes, sometimes you need to materialize this summary stuff for efficiency, but that's the advanced course.)
In Powerpivot, I have a problem in ranking in Table 1, based on Sales and Year. I want to have the result like that:
Year Store Sales **Rank**
2013 A 200 3
2013 B 250 2
2013 C 300 1
2014 A 350 2
2014 B 300 3
2014 C 400 1
Which rank function could I use to have this rank result?
Thanks in advance.
Tran,
Probably the smartest way to go is to use the 'X' functions. They can be a bit tricky and non intuitive, yet are extremely powerful.
First, create a simple measure to calculate the total sales:
TotalSales:=SUM(Stores[Sales])
Then, use this formula below to calculate the rank (per store per year):
Rank:=RANKX(ALL(Stores[Store]), [TotalSales])
That should do what you are looking for. Once those two measures are ready, create a new powerpivot table, dray Year and Store onto rows pane and add required values.
ALL function overwrites the applied rows filter and thus allows to calculate rank per year.
The result should look like this:
Hope this helps.
I am building first cube in SSAS 2012 Tabular modeling. I got one fact table contains following columns
TermDate StudentKey PaperKey marks CumulativeNoOfStudents
20100601 1 1 70 2
20100601 2 1 70 2
20100601 3 1 69 3
20100601 4 2 68 1
Now i need to generate Cumulative Number Of Students (5th column) as an output (calculated column) against each row using DAX.
Can someone help me to build the DAX formula please.
On the basis that your StudentKey is numeric, sequential and unique you can use the following:
=CALCULATE(COUNTROWS(Table), FILTER(Table,Table[StudentKey]<=EARLIER(Table[StudentKey]))
Assuming your table is called 'Table'
HTH
Jacob
on the basis of some assumption like studentkey is numeric and your date table is DimDate with date as unique column, and fact table name as FactStudent can use the below formula also.
Cumalative No of Students :=CALCULATE (CountRows(FactStudent), FILTER(ALL(DimDate[Date]), DimDate[Date] <= MAX(DimDate[Date])))
Wondering if anyone can help with the code for this.
I want to query the data and get 2 entries, one for YTD previous year and one for this year YTD.
Only way I know how to do this is as 2 separate queries with where clauses.. I would prefer to not have to run the query twice.
One column called DatePeriod and populated with 2011 YTD and 2012YTD, would be even better if I could get it to do 2011YTD, 2012YTD, 2011Total, 2012Total... though guessing this is 4 queries.
Thanks
EDIT:
In response to help clear a few things up:
This is being coded in MS SQL.
The data looks like so: (very basic example)
Date | Call_Volume
1/1/2012 | 4
What I would like is to have the Call_Volume summed up, I have queries that group it by week, and others that do it by month. I could pull all the dailies in and do this in Excel but the table has millions of rows so always best to reduce the size of my output.
I currently group by Week/Month and Year and union all so its 1 output. But that means I have 3 queries accessing the same table, large pain, very slow not efficient and that is fine but now I also need a YTD so its either 1 more query or if I could find a way to add it to the yearly query that would ideal:
So
DatePeriod | Sum_Calls
2011 Total | 40
2011 YTD | 12
2012 Total | 45
2012 YTD | 15
Hope this makes any sense.
SQL is built to do operations on rows, not columns (you select columns, of course, but aggregate operations are all on rows).
The most standard approach to this is something like:
SELECT SUM(your_table.sales), YEAR(your_table.sale_date)
FROM your_table
GROUP BY YEAR(your_table.sale_date)
Now you'll get one row for each year on record, with no limit to how many years you can process. If you're already grouping by another field, that's fine; you'll then get one row for each year in each of those groups.
Your program can then iterate over the rows and organize/render them however you like.
If you absolutely, positively must have columns instead, you'll be stuck with something like this:
SELECT SUM(IF(YEAR(date) = 2011, sales, 0)) AS total_2011,
SUM(IF(YEAR(date) = 2012, total_2012, 0)) AS total_2012
FROM your_table
If you're building the query programmatically you can add as many of those column criteria as you need, but I wouldn't count on this running very efficiently.
(These examples are written with some MySQL-specific functions. Corresponding functions exist for other engines but the syntax would be a little different.)