datamart qlikview

[#1]

Question1:

hey everyone,

I have this table in sql server as u see below:

Then I import this table with its data to qlikview  but I want to realize this Datamart by taking the informations from the columns which are in this unique table:

If I can do that, could you guide me how we create Damarts in Qlikview ?

QUESTION 2 :

I have two tables like below, sometimes some informations does not exist is the second table that is why i need to calculate the difference between them

I would like to have a graphe= like this: which I can see at the same time

• The number of employees in table 1
• The number of employees in table two
• And the difference between number of employees in table 2 and numbers of employees in table 1

And when I qlick in a entity  name in qlikview dashboard I want to see of course in the graph the numbers adequate to this entity

Thank you so much

[swuehl]

I haven't fully understood your first question, could you explain this a bit more in detail?

Regarding your second question, you can concatenate your two tables and distinguish between them by creating a new field SOURCE:

Tables:

LOAD Entity,

          Employee,

          'Table 1' as Source

FROM Table1;

LOAD Entity,

          Employee,

          'Table 2' as Source

FROM Table2;

Tables get auto-concatenated when they show the same number of fields and field names.

Then create a chart in your front end with dimension Source (and if you want, Entity) and =Sum(Employee) as expression.

[#3]

Sometimes in the second table there are also wrong data like Entity that does not exist, when i concatenate the two tables by the name of the column: Entity and I add the field ENTITY in the dashboard as u can see below

I get the concatenation of the two ENTITY name's that exist in table 1 + table 2 but i want to see just the ENTITY's name that are in the table 1. how can I do that please?

[swuehl]

You should see the ENTITY values in the list box limited to the values of table 1 when you select 'Table 1' in field Source.

Of course, it depends on your analysis requirements if this approach is suitable for you.

If you focus on comparing the values of the two tables, e.g. for analyzing the data quality, I think it should be a reasonable one.