I'm having an issue where the figures pulled from Analytics are different in a table format than the time series.
As you can see in the image below the 'Nutzer' (user) value in the table for Sep 2019 is 6692 but on the time series is 7789. This then affects the calculated values for 'Umsatz pro Nutzer'.
Does anyone know why this happens and how to stop it?
I think the most likely answer is that there is a filter active on one or both of the objects that is altering the displayed data.
To test this out, create a copy of the sheet and delete the chart. Then make a copy of your table and change it to a time series using the chart options. I just did this process using a connection to the GA property for our mobile app and I see identical data for users for both the table and the time series.
I have a workbook in which a variable number of rows of data (one per employee) are entered each week on one sheet (DATA ENTRY), and then stored on another sheet (LOG) with the help of a macro that is executed every time the file is saved.
To be able to then retrieve and review employee data for a specific week, I need a column of helper cells in which all the unique distinct dates (weeks) are listed.
I currently do this with the following array formula:
{=IFERROR(INDEX($B$2:$B$1600, MATCH(0,COUNTIF($K$1:K1, $B$2:$B$1600), 0)),"")}
This all works brilliantly, except that I found that this one specific formula slows my file down tremendously. When the file is saved (which triggers data to be copied over to the LOG sheet), it can take up to 10 seconds to process. When this array formula is disabled, it is pretty much instantaneous.
Limiting it to run over 1600 rows helped significantly (it took much longer before when I had it set to 20.000), but it is still not enough and I can't really have this check less than 1600 rows.
Any creative solutions to either make this formula run faster, or to get to the same result (a list of unique distinct dates from a large list of dates) without using an array formula?
Thanks!
You could use Power Query (Get & Transform Data) to populate your list of unique dates.
I have two different data sets using two different SQL queries. Essentially one data set is day/caller stats rolled up the other set is call data. So each call data set rolls up to get their day/caller data.
I needed to separate these two queries for performance because I needed one extract and one parameterized custom query for the call data. So essentially I will always bring in this month of data and last month for the day/caller data.
What I need to do is create one dashboard, that has the caller and all of their stats aggregated for the time period. Then I need to be able to click a row to prompt all the call data in a different sheet on the same dashboard
I am at the home stretch and need a way to connect these two sheets and update the call data. Right now I only have a parameter for the Unique ID of the callers not time, I bring in all the same days of calls even though it is really not needed. In a perfect world I will click the report caller and my second query will update to the appropriate day range and Unique ID and produce only that callers calls. My problem right now is no matter what I do I cannot create the one sheet to update the second call sheet. I have successfully created a manually functioning report but I need the action to filter to a timer period and the specific caller.
Let me know if you have any feedback. My two issues are creating two separate queries caller data (225k rows help in export) call data (7 million rows if unfiltered) which needs to be a live connection so when sheet is clicked the parameters will update and those calls will populate. Anything would help!
The solution i can think of is to use an action filter and there is an option below to select the fields to map between the sheets.Choose selected fields instead of all fields and map the id and time between the two data sources.
Apart from this i dont really get what the issue is.If you need further clarifications please rephrase your questions and provide examples and your data structure.
i need to find data between 2 date's and time's.
i use one field for date , and one field for time.
is it be better to use only one field for date & time ?
i see that it came in dd/mm/yyyy hh:mm:ss format that
can contain date and time.
this question is for acceess and for sql-server
thank's in advance
In nearly all circumstances, date and time are needed together. Both Access and SQL server have a date/time data type. In Access, even if you specify the format as time, you can show a date. This is because all datetime data is stored as a number, and time is the decimal portion:
Say I store data: 10:31:46, I can type lines in the immediate window that illustrate the storage of datetime, like so:
?CDec(DlookUp("TimeFormattedField", "Test"))
0.438726851851852
?Year(DlookUp("TimeFormattedField", "Test"))
1899
?Format(dlookup("F4", "Table2"),"dd/mm/yyyy")
30/12/1899
This is because zero (0) is a valid date.
It is very easy to get the different portions of a datetime field, so store datetime as a single fields, because that is what you are going to get, anyway.
I like to store date and time separately. In general, I almost never need time in my apps. One case where I store them separately is in some of my logging routines. This is mostly because I only ever query on dates and never on date+time.
If you need to query on both date and time, then storing them separately is really problematic, because then you have to concatenate two fields for comparison, and that means your criteria won't use any indexes on the two fields. This may not be an issue for a few thousand records, but for anything above that, it can quickly become quite a performance drag. It's also a major issue if you're using a server back end, since all the rows will have to be pulled across the wire, instead of Access/Jet/ACE being able to hand off the selection to the server.
depends on the requirement. If you are using sql server 2008+ then if you store in separate is not a problem, as well as it is as easy option to write the query
I have a huge database (800MB) which consists of a field called 'Date Last Modified' at the moment this field is entered as a text data type but need to change it to a Date/Time field to carry out some queries.
I have another exact same database but with only 35MB of data inside it and when I change the data type it works fine, but when I try to change data type on big database it gives me an error:
Micorosoft Office Access can't change the data type.
There isn't enough disk space or memory
After doing some research some sites mentioned of changing the registry file (MaxLocksPerFile) tried that as well, but no luck :-(
Can anyone help please?
As John W. Vinson says here, the problem you're running into is that Access wants to hold a copy of the table while it makes the changes, and that causes it to exceed the maximum allowable size of an Access file. Compacting and repairing might help get the file under the size limit, but it didn't work for me.
If, like me, you have a lot of complex relationships and reports on the old table that you don't want to have to redo, try this variation on #user292452's solution instead:
Copy the table (i.e. 'YourTable') then paste Structure Only back
into your database with a different name (i.e. 'YourTable_new').
Copy YourTable again, and paste-append the data to YourTable_new.
(To paste-append, first paste, and select Append Data to Existing
Table.)
You may want to make a copy of your Access database at this point,
just in case something goes wrong with the next part.
Delete all data in YourTable using a delete query---select all
fields, using the asterisk, and then run with default settings.
Now you can change the fields in YourTable as needed and save
again.
Paste-append the data from YourTable_new to YourTable, and check
that there were no errors from type conversion, length, etc.
Delete YourTable_new.
One relatively tedious (but straightforward) solution would be to break the big database up into smaller databases, do the conversion on the smaller databases, and then recombine them.
This has an added benefit that if, by some chance, the text is an invalid date in one chunk, it will be easier to find (because of the smaller chunk sizes).
Assuming you have some kind of integer key on the table that ranges from 1 to (say) 10000000, you can just do queries like
SELECT *
INTO newTable1
FROM yourtable
WHERE yourkey >= 0 AND yourkey < 1000000
SELECT *
INTO newTable2
FROM yourtable
WHERE yourkey >= 1000000 AND yourkey < 2000000
etc.
Make sure to enter and run these queries seperately, since it seems that Access will give you a syntax error if you try to run more than one at a time.
If your keys are something else, you can do the same kind of thing, but you'll have to be a bit more tricky about your WHERE clauses.
Of course, a final thing to consider, if you can swing it, is to migrate to a different database that has a little more power. I'm guessing you have reasons that this isn't easy, but with the amount of data you're talking about, you'll probably be running into other problems as well as you continue to use Access.
EDIT
Since you are still having some troubles, here is some more detail in the hopes that you'll see something that I didn't describe well enough before:
Here, you can see that I've created a table "OutputIDrive" similar to what you're describing. I have an ID tag, though I only have three entries.
Here, I've created a query, gone into SQL mode, and entered the appropriate SQL statement. In my case, because my query only grabs value >= 0 and < 2, we'll just get one row...the one with ID = 1.
When I click the run button, I get a popup that tells/warns me what's going to happen...it's going to put a row into a new table. That's good...that's what we're looking for. I click "OK".
Now our new table has been created, and when I click on it, we can see that our one line of data with ID = 1 has been copied over to this new table.
Now you should be able to just modify the table name and the number values in your SQL query, and run it again.
Hopefully this will help you with whatever tripped you up.
EDIT 2:
Aha! This is the trick. You have to enter and run the SQL statements one at a time in Access. If you try to put multiple statements in and run them, you'll get that error. So run the first one, then erase it and run the second one, etc. and you should be fine. I think that will do it! I've edited the above to make it clearer.
Adapted from Karl Donaubauer's answer on an MSDN post:
Switch to immediate window (Ctl + G)
Execute the following statement:
DBEngine.SetOption dbMaxLocksPerFile, 200000
Microsoft has a KnowledgeBase article that addresses this problem directly and describes the cause:
The page locks required for the transaction exceed the MaxLocksPerFile value, which defaults to 9500 locks. The MaxLocksPerFile setting is stored in the Windows registry.
The KnowledgeBase article says it applies to Access 2002 and 2003, but it worked for me when changing a field in an .mdb from Access 2013.
It's entirely possible that in a database of that size, you've got text data that won't convert to a valid Date/Time.
I would suggest (and you may hate me for this) that you export all those prospective date values from "Big" and go through them (perhaps in Excel) to see which ones are not formatted the way you'd expect.
Assuming that the error message is accurate, you're running up against a disk or memory limitation. Assuming that you have more than a couple of gigabytes free on your disk drive, my best guess is that rebuilding the table would put the database (including work space) over the 2 gigabyte per file limit in Access.
If that's the case you'll need to:
Unload the data into some convenient format and load it back in to an empty database with an already existing table definition.
Move a subset of the data into a smaller table, change the data type in the smaller table, compact and repair the database, and repeat until all the data is converted.
If the error message is NOT correct (which is possible), the most likely cause is a bad or out-of-range date in your text-date column.
Copy the table (i.e. 'YourTable') then paste just its structure back into your database with a different name (i.e. 'YourTable_new').
Change the fields in the new table to what you want and save it.
Create an append query and copy all the data from your old table into the new one.
Hopefully Access will automatically convert the old text field directly to the correct value for the new Date/Time field. If not, you might have to clear out the old table and re-append all the data and use a string to date function to convert that one field when you do the append.
Also, if there is an autonumber field in the old table this might not work because there is no way to ensure that the old autonumber values will line up with the new autonumber values that get assigned.
You've been offered a bunch of different ways to get around the disk space error message.
Have you tried adding a new field to your existing table using Date data type and then updating the field with the value the existing string date field? If that works, you can then delete the old field and rename the new one to the old name. That would probably take up less temp space than doing a direct conversion from string to date on a single field.
If it still doesn't work, you may be able to do it with a sceond table with two columns, the first long integer (make it the primary key), the second, date. Then append the PK and string date field to this empty table. Then add a new date field to the existing table, and using a join, update the new field with the values from the two-column table.
This may run into the same problem. It depends on number of things internal to the Jet/ACE database engine over which we have no real control.