I am needing to Calculate the start/end Balances by day for each Site/Department.
I have a source table call it “Source” that has the following fields:
Site
Department
Date
Full_Income
Income_To_Allocate
Payments_To_Allocate
There are 4 Sites (SiteA/SiteB/SiteC/SiteD), Sites B-D have only 1 department and Site A has 10 departments.
This table is “mostly” a daily summary. I say “mostly” as the daily detail from 2018 was lost and instead we just have the monthly summary inputted as one entry on the last day of the month. For 2018 there is only data going back to September. From 1/1/2019 the summary is actually daily.
Any Income in the Full_Income field will be given to that Site/Department at 100% value.
Any Income in the Income_To_Allocate field will be spread among all the Site/Departments using the below logic:
(
(Prior_Month_Site_Department_ Balance+ This_Month_Site_Department_Full_Income)
/
(Prior_Month_All_Department_Balance + This_Month_All_Department_Full_Income)
)
*
(This_Month_All_Department_Income_to_Allocate)
Any Payments in the Payments_to Allocate) field will be spread among all the Site/Departments using the below logic:
(
(Prior_Month_Site_Department_ Balance+ This_Month_Site_Department_Full_Income)
/
(Prior_Month_All_Department_Balance + This_Month_All_Department_Full_Income)
)
*
(This_Month_All_Department_Payments_to_Allocate)
The idea behind these pieces of logic is to spread the allocated pieces based on the % of business each Site/Department did when looking at the Full_Income data.
The Balance would be calculated with this logic:
Start Balance:
Prior day Ending Balance
Ending Balance:
Prior day Ending Balance + (Site_Department_Full_Income) + (Site_Department_Allocated_Income)- (SiteDepartment_Allocated_Income)
I have tried to do things using the lag function to grab the prior info that I am needing for these calculations. I always get real close but I always wind up stuck on the fact the Ending Balance is calculated using the post spread values for the allocated income and reseeds while the calculation for the spread is using the prior month balance info. This ends up being almost circular logic but with a finite start point. I am at a loss for how to make this work.
I am using SQL Server 2012. Let me know if you need any more details.
Related
Problem Statement: I need to find out Over Due start date and from that i need to calculate number of Over due days. I know how to do for Over due days count, but i am not able to find a way to figure out for Over due start date.
Example: Let us say a customer did not pay for 4th November 2017, 4th December 2017, 4th Jan 2018, 4th Feb 2018. Now for these There were 4 Zero collection records placed in Collections table and 4 records placed in Over Due Collections table with D Flag. Now on 8th Feb Customer Paid an installment then the respective payment record has been placed in Collections table and another record in Over due collections with C flag. Since this payment gets adjusted for 4th November 2017 the Over due start date will be 4th December. Suppose if the customer did not pay then it will be 4th November 2017 as the Over due start date.
I have tables as follows for a Loan Management System:
Schedule (Payment Schedule): Which will have all the Installments, with the dates adn the respective amounts to be paid for each month.
Schema: LoanNo, Schedule Date, Installment No, Principle, Interest.
Collections (Payment Collections) for each month which has been collected. Suppose if the payment not received, A record placed with the respective date and with Zero amount. and another record will be placed in Over due collections table with D flag with the respective amounts. If there is any collection happens, then another record will be inserted with the flag C which represents collections.
Schema: LoanNo, PaymentReceived Date, Principle, Interest
Over Due Collections (Which there will be a record placed if there is a Due)
Schema: LoanID, Flag(D/C), Date, Principle, Interest
Please do suggest and guide me to write a proper query for this
it's interesting yet easy problem. you can tackle by calculating running sum of the amount and then compare with total payments by the customer. Take all the records having running sum greater than total payment. and choose minimum date out of it.
let me know if require further help I will give you SQL query. But you should try by your own
Edit 1
this will provide you running_sum
_______Subquery1_______
select a.LoanNO,a.Scheduledate,a.Amount,sum(b.amount)run_sum from
Paymentschedule a
join PayamentSchedule b
on a.LoanNo=b.LoanNo and a.ScheduleDate>b.ScheduleDate and
a.ScheduleDate<=now() group by 1,2,3
total collection against loan
_______subquery 2_____
select LoanNo,sum(amount)total collection from collection group by 1
now
select a.LoanNo,min(ScheduleDate) overduestartdate from subquery1 join subquery2 on
a.LoanNO=b.LoanNO
and a.run_sum>b.Collection group by 1
modify according to your schema
Background: I have a column in a Customer dimension with a static date(e.g '2013-01-01').
This column is the result of a calculation that gets the first transaction date ever made by that certain customer. This customer dimension is linked to a fact table containing reportdate as a date column linked to a date dimension.
Goal: I want to make a calculated measure that, based on a sum of amount measure, calculates the result based on a given period between start_date(First transaction date), end_date (first transaction date + 6 months).
All i get is "cannot be determined in the current context" warnings and cannot get my head around to fix it.
All help is welcome!
Thanks in advance,
/Blixter
SOLVED I replicated the logic from the calculated measure found in the Customer table.
=CALCULATE([SumAmount];DATESBETWEEN(DimDate[Date];FIRSTDATE(FactTable[Reportdate]);DATEADD(FIRSTDATE(FactTable[Reportdate]);5;MONTH)))
I am making a basic hospital management system in Access 2013.I have two tables named "Bed" and "Receipt".
Bed(BedID,AssignedDate,PatientID,DischargeDate,BedCharges)
Reciept(ReceiptID,PatientID,BedCharges)
I want to calculate "BedCharges" by calculating the number of days using "AssignedDate" and "DischargeDate" and then multiplying with a constant amount of charges per day.
Also the BedCharges calculated in "Bed" Table also needs to be in the "Receipt" table.
How can I count the number of days and then calculate the "BedCharges" in both the tables?
I want to model a fact table for our users to help us calculate DAU (Daily active Users), WAU (Weekly active users) and MAU (Monthly active users).
The definitions of these measures are as follows:
1. DAU are users who is active every day during last 28 days.
2. WAU are users who are active at least on one day in each 7 days period during last 28 days
3. MAU are users who are active at least 20 days during last 28 days
I have built a SSAS cube with my fact table and user dimension table as follows
Fact : { date, user_id, activity_name}
Dimension: { date, user_id, gender, age, country }
Now I want to build a cube over this data so that we can see all the measures in any given day for last 28 days.
I thought of initially storing 28 days of data for all users in the SQL server and then do count distinct on date to see which measures they fall into.. but this proved very expensive since the data per day is huge..almost 10 millions rows.
So my next thought was to model the fact table (before moving it to SQL) such that it has a new column called "active_status" which is a 32 bit binary type column.
Basically, I'll store a binary number (or decimal equivalent) like 11000001101111011111111111111 which has a bit set on the days the user is active and off on the days user is not active.
This way I can compress 28 days worth of data in a single day before loading into data mart
Now the problem is , I think MDX doesn't support bitwise operations on columns in the expressions for calculated members like regular SQL does. I was hoping to create calculated measures daily_active_users, weekly_active_users and monthly_active_users using MDX that looks at this active_status bit for the user and does bitwise operation to determine the status.
Any suggestions on how to solve this problem? if MDX doesn't allow bitwise, what else can I do SSAS to achieve this.
thanks for the help
Additonal notes:
#Frank
Interesting thought about using a view to do the conversion from bitset to a dimension category..but I'm afraid it won't work. Because I have few dimensions connected to this fact table that have many-many relationships..for ex: I have a dimension called DimLanguage and another dimension called DimCountry and they have many-many relationship. And what ultimately I would like to do in the cube is to calculate the DAU/WAU/MAU which are COUNT(DISTINCT UserId) based on the combination of dimensions. So for ex; If a user is not MAU for dimension country US because he is only active 15 days out of 28 ....but he will be considered
You do not want to show the bitmap data to the users of the cube, but just the categories DAU, WAU, MAU, you should do the conversion from bitmap to category on data loading time. Just create a dimension table containing e. g. the following data:
id category
-- --------
1 DAU
2 WAU
3 MAU
Then define a view on your fact table that evaluates the bitmap data, and for each user and each date just calculates the id value of the category the user is in. This is then conceptually a foreign key to the dimension table. Use this view instead of the fact table in your cube.
All the bitmap evaluations are thus done on the relational side, where you have the bit operators available.
EDIT
As your requirement is that you need to aggregate the bitmap data in Analysis Services using bitwise OR as the aggregation method, I see no simple way to do that.
What you could do, however, would be to have 28 single columns, say Day1 to Day28, which would be either 0 or 1. These could be of type byte to save some space. You would use Maximum as aggregation method, which is equivalent to binary OR on a single bit.
Then, it would not be really complex to calculate the final measure, as we know the values are either zero or one, and thus we can just sum across the days:
CASE
WHEN Measures.[Day1] + ... + Measures.[Day28] = 28 THEN 'DAU'
WHEN Measures.[Day1] + ... + Measures.[Day7] >= 1 AND
Measures.[Day8] + ... + Measures.[Day14] >= 1 AND
Measures.[Day15] + ... + Measures.[Day21] >= 1 AND
Measures.[Day22] + ... + Measures.[Day28] >= 1 THEN 'WAU'
WHEN Measures.[Day1] + ... + Measures.[Day28] >= 20 THEN 'MAU'
ELSE 'Other'
END
The order of the clauses in the CASE is relevant, as the first condition matching is taken, and your definitions of WAU and MAU have some intersection.
If you have finally tested everything, you would make the measures Day1 to Day28 invisible in order not to confuse the users of the cube.
I have a table named "Historical_Stock_Prices" in a MS Access database. This table has the columns: Ticker, Date1, Open1, High, Low, Close1, Volume, Adj_Close. The rows consist of the data for each ticker for every business day.
I need to run a query from inside my VB.net program that will return a table in my program that displays the growth rates for each quarter of every year for each ticker symbol listed. So for this example I would need to find the growth rate for GOOG in the 4th quarter of 2012.
To calculate this manually I would need to take the Close Price on the last BUSINESS day of the 4th quarter (12/31/2012) divided by the Open Price of the first BUSINESS day of the 4th quarter (10/1/2012). Then I need to subtract by 1 and multiply by 100 in order to get a percentage.
The actual calculation would look like this: ((707.38/759.05)-1)*100 = -6.807%
The first and last days of each quarter may vary due to weekend days.
I cannot come up with the correct syntax for the SQL statement to create a table of Growth Rates from a table of raw Historical Prices. Can anyone help me with the SQL statment?
Here's how I would approach the problem:
I'd start by creating a saved query Access named [Stock_Price_with_qtr] that calculates the year and quarter for each row:
SELECT
Historical_Stock_Prices.*,
Year([Date1]) AS Yr,
Switch(Month([Date1])<4,1,Month([Date1])<7,2,Month([Date1])<10,3,True,4) AS Qtr
FROM Historical_Stock_Prices
Then I'd create another saved query in Access named [Qtr_Dates] that finds the first and last business days for each ticker and quarter:
SELECT
Stock_Price_with_qtr.Ticker,
Stock_Price_with_qtr.Yr,
Stock_Price_with_qtr.Qtr,
Min(Stock_Price_with_qtr.Date1) AS Qtr_Start,
Max(Stock_Price_with_qtr.Date1) AS Qtr_End
FROM Stock_Price_with_qtr
GROUP BY
Stock_Price_with_qtr.Ticker,
Stock_Price_with_qtr.Yr,
Stock_Price_with_qtr.Qtr
That would allow me to use the following query in VB.NET (or C#, or Access itself) to calculate the quarterly growth rates:
SELECT
Qtr_Dates.Ticker,
Qtr_Dates.Yr,
Qtr_Dates.Qtr,
(([Close_Prices]![Close1]/[Open_Prices]![Open1])-1)*100 AS Qtr_Growth
FROM
(
Historical_Stock_Prices AS Open_Prices
INNER JOIN Qtr_Dates
ON (Open_Prices.Ticker = Qtr_Dates.Ticker)
AND (Open_Prices.Date1 = Qtr_Dates.Qtr_Start)
)
INNER JOIN
Historical_Stock_Prices AS Close_Prices
ON (Qtr_Dates.Ticker = Close_Prices.Ticker)
AND (Qtr_Dates.Qtr_End = Close_Prices.Date1)