I make a database for theatre tickets selling system. There are tables with theatres, spectacles and sessions of spectacles (one spectacle can be showed many times). In table with sessions there is a date field. I need to make a form, where user can choose a theatre and a month, and will get a report with a list of sessions in chosen theatre for chosen month. Does anyone know how to do it?
i guess you are searching for the Month Function.So when you select a month you need to perform this on the query :
WHERE Month(DateOfSession) = " & me.cboSelectMonth
Related
I'm working with a list of engagement scores for each company.
SELECT pel.companyProfileID, pel.engagementScore, pel.createTimestamp
FROM partnerEngagementLog pel
A snippet of results for one company:
I'm trying to produce a cohort analysis table with:
A single row for each companyProfileID.
Columns for each engagementScore by latest, second latest, etc.
The issue is that time between timestamps varies and I'm having trouble figuring out how to select properly. Put another way, what I need is columns for "last score per companyID", "second-to-last", "third-to-last", etc. that are based on absolute row positioning and not date range.
Any help would be greatly appreciated, still learning SQL on the side as I develop my business.
We are trying to calculate average stock from a movements table in a single sql sentence.
As far as we are, no problem with what we thought was a standard approach, instead of adding up the daily stock and divide by the number of days, as we don’t have daily stock, we simply add (movements*remaining days) :
select sum(quantity*(END_DATE-move_date))/(END_DATE-START_DATE)
from move_table
where move_date<=END_DATE
This is a simplified example, in real life we already take care of the initial stock at the starting date. Let’s say there are no movements prior to start_date.
Quantity sign depends on move type (sale, purchase, inventory, etc).
Of course this is done grouping by product, warehouse, ... but you get the idea.
It works as expected and the calculus is fine.
But (there is always a “but”), our customer doesn’t like accounting days when there is no stock (all stock sold out). So, he doesnt like
Sum of (daily_stock) / number_of_days (which is what we calculate using a diferent math)
Instead, he would like
Sum of (daily stock) / number_of_days_in_which_stock_is_not_zero
For sure we can do this in any programming language without much effort, but I was wondering how to do it using plain sql ... and wasn’t able to come up with a solution.
Any suggestion?
Consider creating a new table called something like Stock_EndOfDay_History that has the following columns.
stock#
date
stock_count_eod
This table would get a new row for each stock item at the start of a new day for the prior day. Rows could then be purged from this table once the applicable date value went outside the date window of interest.
To get the "number_of_days_in_which_stock_is_not_zero", use this.
SELECT COUNT(*) AS 'Not_Zero_Stock_Days' FROM Stock_EndOfDay_History
WHERE stock# = <stock#_value>
AND <date_window_clause>
Other approaches might attempt to just add a new column to the existing stock table to maintain a cumulative sum of the " number_of_days_in_which_stock_is_not_zero". But inevitably, questions will be asked as to how did the non-zero stock days count get calculated? Using this new table approach will address those questions better than the new column approach.
I am trying to apply some Time Intelligence functions in my PowerPivot workbook concerning projects and money received for them. I have three relevant tables; Matters, Payments, and a Date Table.
Each matter has a creationDate, and a closureDate(from a linked table). Likewise, each payment has a date. I have reporting set up decently, but am now trying to use Time intelligence to filter this a bit more clearly.
How can I set a PowerPivot Pivot Table up so that the only Matters which show are those which existed within the period selected. e.g. If I select a slicer for 2014, I don't want to show a matter created in 2015, or one which was closed in 2013. The matter should have been active during the period specified.
Is this possible?
You want to show all the matters EXCEPT those where the CreationDate is after the upper limit of the date range you are looking at or the ClosureDate is before the lower limit of the date range you are looking at.
Assuming you have a data structure like this, where the left-hand table is the Matters and the right-hand one is the Payments:
If you have a calculated field called [Total Payments] that just adds up all the payments in the Payments table, a formula similar to this would work:-
[Payment in Range]:=IF(OR(MIN(Matters[Creation Date])>MAX('Reporting Dates'[Date]),MAX(Matters[Closure Date])<MIN('Reporting Dates'[Date])),BLANK(),[Total Payments])
Here is the result with one month selected in the timeline:
Or with one year selected in the year slicer:
NOTE: in my example, I have used a disconnected date table.
Also, you will see that the Grand Total adds up all the payments because it takes the lowest of all the creation dates and the highest of all the closure dates to determine whether to show a total payment value. If it is important that the Grand Total shows correctly, then an additional measure is required:
[Fixed Totals Payment in Range]:=IF(COUNTROWS(VALUES(Matters[Matter]))=1,[Payment in Range],SUMX(VALUES(Matters[Matter]),[Payment in Range]))
Replace the [Payment in Range] in your pivot table with this new measure and the totals will show correctly, however, this will only work if Matters[Matter] is used as one of the fields in the pivot table.
Use filters & the calculate function.
So, if you're Summing payments, it would look like.....
Payments 2014:= CALCULATE( SUM([Payments]), DateTable[Year]=2014)
The Sum function takes the entirety of payments & the filter function will only capture payments w/in 2014, based on the data connected to your date table.
I am working on an Hotel DB, and the booking table changes a lot since people book and cancel reservation all the time. Trying to find out the best way to convert the booking table to a fact table in SSAS. I want to be able to get the right statsics from it.
For example: if a client X booked a room on Sep 20th for Dec 20th and canceled the order on Oct 20th. If I run the cube on the month of September (run it in Nov) and I want to see how many rooms got booked in the month of Sep, the order X made should be counted in the sum.
However, if I run the cube for YTD calculation (run it in Nov), the order shouldn't be counted in the sum.
I was thinking about inserting the updates to the same fact table every night, and in addition to the booking number (unique key) and add revision column to the table. So going back to the example, let say client X booking number is 1234, the first time I enter it to the table will get revision 0, in Oct when I add the cancellation record, it will get revision 1 (of course with timestamp on the row).
Now, if I want to look on any piroed of time, I can take it by the timestamp and look at the MAX(revision).
Does it make sense? Any ideas?
NOTE: I gave the example of cancelling the order, but we want to track another statistics.
Another option I read about is partitioning the cubes, but do I partition the entire table. I want to be able to add changes every night. Will I need to partition the entire table every night? it's a huge table.
One way to handle this is to insert records in your fact table for bookings and cancellations. You don't need to look at the max(revision) - cubes are all about aggregation.
If your table looks like this:
booking number, date, rooms booked
You can enter data like this:
00001, 9/10, 1
00002, 9/12, 1
00001, 10/5, -1
Then your YTDs will always have information accurate as of whatever month you're looking at. Simply sum up the booked rooms.
Let's think we have 100+ hotels, and each hotel has at least more than 3 room types.
I want to hold hotel's capacity for one year in the past and one year in the future. How should i design the database for easiest use.
Example:
A hotel has 30 rooms. 10 x "Standard
room", 10 x "Duplex Room", 10 x "Delux
room" I will keep this example on
standard rooms. Today is: 13.01.2011 I
want to keep records from 13.01.2010
to 13.01.2012 What i will store in
database is available rooms. Something
like this(for standard room):
13.01.2011: 10
14.01.2011: 9 (means 1 standard room sold for this day)
15.01.2011: 8 (means 2 standard rooms sold for this day)
16.01.2011: 10 (all available for this day)
17.01.2011: 7 (means 3 standard rooms sold for this day)
18.01.2011: 10
etc...
Thanks in advance.
Let me try to summarize your question to see if I understand it properly:
You have a set of Hotels. Each Hotel
has a set of Rooms. Each Room belongs
to one of a number of possible Room
Types. The lowest level of detail
we're interested in here is a Room.
This suggests a table of Hotels, a lookup table of Room Types, and a table of Rooms: each Room will have a reference to its associated Hotel and Room Type.
For any given day, a room is either
booked (sold) or not booked (let's
leave off partial days for simplicity
at this point). For each day in the
year before and the year after the
current day, you wish to know how many
rooms of each type were available (non-booked) at
each hotel.
Now, since hotels need to be able to look at bookings individually, it's likely you would maintain a table of bookings. But these would typically be defined by a Room, a Start Date, and a number of Nights, which isn't ideal for your stated reporting purposes: it isn't broken down by day.
So you may wish to maintain a "Room Booking Log" table, which simply contains a record for each room booked on each day: this could be as simple as a datestamp column plus a Room ID.
This sort of schema would let you generate the output you're describing relatively easily via aggregate queries (displaying the sum of rooms booked per day, grouped by hotel and room type, for example). The model also seems like it would lend itself to an OLAP cube.
I did a homework question like this once. Basically you need at least 3 tables: one which holds the rooms, one which holds the reservations, and another table that links the too because its not a specific room that is reserved at a given time, its a specific type of room.