Create a database
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Hi all :)
I am kind of stuck with a problem. I would like to build a database which is growing with time.
The data is always strcutured in the same way: ten columns with the same headers followed by columns with "dates" as names.
For example:
When updating the data now. My data table start with 10 columns of headers and the first following column is then "01-01-2000".
Last year, the table started with 10 columns of headers (same as now) and the first following column is then "01-01-1998".
I will try to have a workflow that find the columns which are not in the current data anymore and adds them before the current dates start.
So the result would be:
Header 1 .... Header 10; 01.01.1998; 01.01.1999; 01.01.2000 ...
Whereas 01.01.200 comes form the current and the the other two columns from the previous data.
Hope you can undertand my issue.
Thx
Solved! Go to Solution.
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@RRW , could you please clarify what the logic is for the headers that are dates? What determines the dates in those headers this year? what about last year? what about the year before?
What I'm trying to understand is the "how" and "why" the values change from year over year.
This will help me assist you further.
Thanks.
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Determine the purpose of your database. This helps prepare you for the remaining steps.
Find and organize the information required.
Divide the information into tables.
Turn information items into columns.
Specify primary keys.
Set up the table relationships.
Refine your design.
Apply the normalization rules.
Regards,
Rachel
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I use different data inputs (like stock indexes). With the time, the start of the those indexes change: For example: Right now the first available value for the DowJones is from 1950 - in 5 years it might start from 1955. I do not want to lose the 5 years which are missing then.
Therefore I need to detect which fields (in that case 1950 to 1954) are no longer available. And add them to the current dataset.
The structure of those field names is always in a date structure "01-01-1950".
Also a general rule: New datasets will always have more current values. It will never occur that a new dataset conatins "older" data then the dataset before.
Hope that helps?
BR
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Hi @RRW
Do you have some column that has unique identifiers for each row? Replace this identifier by the recordID and i think that this gonna work for you.
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