Assuming I have a masterdata pool containing customer data. I want to filter masterdata entities using queryMasterdata.
A masterdata entity - by definition - has 6 filter attributes, 3 string based and 3 numeric, which can be used for filtering with good performance because the values are indexed.
What if I want to filter for customers in that pool using more than 6 criterias of type string?
For instance:
First Name
Last Name
City
Country
State
Street
Occupation
I am aware that some of the criterias should rather be predefined values in a productive scenario for usability reasons. But let's assume all 7 filter criterias are treated as strings. How to model / structure the masterdata to make sure that all criterias are operating on indexed values of masterdata, when there are only 3 string filters available in one masterdata entity?
If you would like to use more than 3 string filters, you may split your masterdata into several pools. You can create separate pools for the person details and the location details or group them according to your preference. Then, you may link the data between the pools by making use of the numeric filters as foreign keys.
Kind Regards,
Ana
Related
Take the public github dataset as an example
SELECT
*
FROM
`bigquery-public-data.github_repos.commits`
LIMIT
2
There are column names like
difference.old_mode
via search:
column:difference.old_mode
will show no results
So, in this case the period isn't actually the column name, its an indication that you're dealing with a complex type (there's a record/struct column of name difference, and within that exists a column named old_mode.
Per search reference there's no special syntax for complex schemas documented.
A suggestion might be to leverage a logical AND operator like column:(difference,old_mode). It's not as precise as specifying the column relationship, but it should return the results you're interested in receiving.
I'm having trouble unmerging cells on the report.
3 Suppliers for the query
I have a SQL query that shows 3 instances of a supplier (left joined to contact) as shown below. However, when running the report for the query the 3 instance of the supplier is merged into one. This is not desirable in my case because when exporting the report to excel, I'd like to be able to sort columns based on other properties, however, this would not be possible due the the merging of the rows. How can I get results to show individually?
Cells are Merged on the report
Within the properties of each Row Group you can specify which columns to group on. You generally don't need a separate group for each field, but that's OK. In your last group, the one called "(Details)", if it is not grouped by anything, it will show one row per line of results from the query. So take a look at what it's grouped by. As long as the rows are in your dataset, the report will group or show them based on how you configure the grouping here. Grouping on nothing means it will show all rows.
Another tip is to align the end of your header textbox with the line of one of your columns. This will prevent it from creating an extra column in Excel for the "City" field.
Your report does not need all of those groupings - the SSRS grouping is not like SQL. You should only group when you want to aggregate data on that field. Normally you might have a company with its address in various fields in one group but you only need to group once on the Company Name or (preferably) ID - not on each field and not a separate group for each. You could then show details of various invoices in other columns that aren't grouped.
But since you want to display the company data on each row, you would not want ANY grouping on the company.
To fix your issues, remove all the groupings (but not the rows) and just leave the detail group (which doesn't have a Grouping).
You can check out MS Docs: Understanding Groups for a better explanation.
Apologies if this has been asked and answered but I haven't managed to find a match.
I have built a spreadsheet that lists all the movies in my collection. In that I have two columns that contain the Genres and four that list up to that number of principle actors like this...
A given genre can appear in either of those two columns D & E. An actor's name in any one of columns G,H,I,J. What I want to be able to do is have a filter that shows all the values across all the relevant columns in a drop-down list, as you get when you filter a single column. In other words, when I click the filter for Genre it shows 'drama' in the drop-down whether 'drama' is in column D or E and if selected shows results where it's in either column. Similar for actors names.
Is it possible to achieve this? I know I can use advanced filter to build an 'OR' query across column D & E but as far as I can see there's no way of making that list the available values across the columns and allow a choice - you have to know in advance what you are looking for.
You should also know I'm running an old release (2007) of Excel so any answer ideally has to work in that version, although if there is a way of doing so in a later release I am still interested in hearing that..
I think you would need to separate genres into 2 columns. say Genres A and Genres B, therefore you could apply filter for these columns
Many database management systems, such as Oracle, SQL Server or even statistical software like SAS, allow having, beside field names, also field labels.
E.g., in DBMS one may have a table called "Table1" with, among other fields, two fields called "income_A" and "income_B".
Now, in the DBMS logic, "income_A" and "income_B" are the field names.
Beside a name, those two fields can also have plain English labels associated to them, which clarify the actual meaning of those two fields; such as "A - Income of households with dependable children where both parents work and they have a post-degree level of education" and "B - Income of empty-nesters households where only one works".
Is there anything like that in Python3 Pandas dataframes?
I mean, I know I can give a dataframe column a "label" (which is, seen from the above DBMS perspective, more like a "name", in the sense that you can use it to refer to the column itself).
But can I also associate a longer description to the column, something that I can choose to display instead of the column "label" in print-outs and reports or that I can save into dataframe exports, e.g., in MS Excel format? Or do I have to do it all using data dictionaries, instead?
It does not seem that there is a way to store such meta info other than in the columns name. But the column name can be quite verbose. I tested up to 100 characters. Make sure to pass it as a collection.
Such a long name could be annoying to use for indexing in the code. You could use loc/iloc or assign the name to a string for use in indexing.
In[10]: pd.DataFrame([1, 2, 3, 4],columns=['how long can this be i want to know please tell me'])
Out[10]:
how long can this be i want to know please tell me
0 1
1 2
2 3
3 4
This page shows that the columns don't really have any attributes to play with other than the lablels.
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.columns.html
There is some more info you can get about a dataframe:
https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.info.html
Okay, hope this question will be clear enough that I can get an answer. Thanks for the help.
The situation is that I am downloading some information into two different spreadsheets which contains orders from two different stores.
The problem is that between these two stores the model numbers (SKU#) for a lot of items are different even though the product is the same. There is no changing that now. I do have a list of equivalencies. For example, I know that 00-XX-55 is the same in Store 1 as 22-FF-33. There isn't a logical equivalency so I would be setting them manually.
My question is if there is any way I can combine data from two sheets and set up manual equivalencies while doing this? Would excel allow me to manage the data in that way I can join the two unequal SKUs
You need a two-column translation table. Once you have this you can manage combined inventory because you can then determine the total inventory of a single item in both stores.
So in a solution do you want to translate all to the store 1 sku, the store 2 sku, or a third warehouse sku? I guess what I am driving at here is that there needs to be a superior synonym to sort of design around.
To build a translation table you would put the original sku (the sku that you will convert from, sort of the inferior number you do not want to go by for purposes of the summarization) into column A and the master sku into column B. We will call this sheet "converter".
You could either have:
A, B
00-XX-55, 22-FF-33
This could normalize everything to the 22- sku. Or you could do this:
A, B
00-XX-55, 123abc
22-FF-33, 123abc
This way if you want to normalize to a third value rather than either of the stores values.
In your inventory page col C is the sku column so in column D put =iferror(vlookup(C, converter!A:B, 2, false), C) and populate that all the way down. Now in each row you have the original and the master sku next to each other in C and D. If the sku was not found in the converter table then it would just use whatever value was in C. You can then build pivots tables using D to group them on.